Master Level Theses

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Here you can find proposals for master thesis (20 CFU for each student). See Project Proposals for other kinds of projects and theses.


Evolutionary Optimization and Stochastic Optimization

Agents, Multiagent Systems, Agencies

Wiki Page: 3D Scene Understanding
FreeCamera.png
Title: 3D Indoor scene understanding and layout reconstruction for a mobile robot in collaboration with UnimiB
Description: The proposed project aims to reconstruct the 3D structural layout of an indoor environment perceived by a mobile robot. From the sensorial data, the robot should be able to reconstruct a geometrical structure of an indoor environment (e.g., an office).

Methods for indoor layout reconstruction must be significantly more tolerant to missing data than their outdoor counterparts, since environments such as offices and apartments exhibit extremely high levels of clutter, which typically results in heavy occlusions of walls and other structures of interest, large-scale artifacts, noise and missing data. The proposed work will be developed in collaboration with IRALAB, the Robotics Lab of University of Milano Bicocca.

The work will be based on an existing project, Free Your Camera (http://www.ira.disco.unimib.it/research/robotic-perception-research/free-your-camera-3d-indoor-scene-understanding-from-arbitrary-camera-motion/) and will be part of a robotic framework based on with ROS and in development at IRALAB.

Tutor: [[FrancescoAmigoni | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 February 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: Robotics

Wiki Page: A firefox extension for semantic annotations
Title: A Firefox extension for semantic annotations
Description: Aim of this project is to develop a Firefox extension, to allow a community of users to annotate resources on the Web using a shared RDF vocabulary.

While browsing the Web, a user should be able to visualize the annotations relative to the page they are visiting, and to add new annotations as well.

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: AI in Racing Games
TORCS2.jpg
Title: AI in Racing Games
Description: This project is focused on TORCS, a state-of-the-art open source racing simulator. From one hand, TORCS represents an ideal bechmark to study Computational Intelligence techniques. On the other hand, Computational Intelligence techniques could be used to improve the game experience in this kind of games. Several projects and theses are available on this topic, please contact us for additional information.

References:

Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Accurate AR Marker Location
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Title: C++ Library for accurate marker location based on subsequent pnp refinements
Description: ARTags, QR codes, Data Matrix, are visual landmark used for augmented reality, but they could be used for robotics as well. A thesis has already been done on using data matrix for robot localization and mapping, but improvements are required in terms generality, accuracy and robustness of the solution. The goal is thuss to:
  • increase the number of markers supported by the system (ARTag + QR codes)
  • increase the accuracy of the detection and localization of the marker
  • test different algorithms for the solution of the perspective from n points problem

Material:

  • papers on PnP algorithms, OpenCV,
  • Matlab code with three PnP algorithms implementations
  • C++ libraries for marker detection (to be found and evaluated)

Expected outcome:

  • C++ library to the robust localization of artificial markers
  • a ROS node performing accurate ARTag localization
  • a comparison of Tags and algorithms in a real world scenario
  • The use of this library in a SLAM framework (Thesis)

Required skills or skills to be acquired:

  • background on computer vision and image processing
  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 5 - 10
Research Area: Computer Vision and Image Analysis
Research Topic: None

Wiki Page: Annotation aggregators from social applications
Title: Annotation aggregators from social applications
Description: Annotations are metadata published about a resource, such as tags in del.icio.us, comments on stumbleupon.com, or twines on Twine.com. One of the main problems of these annotations is that they are not expressed in a standard format: thus, any tool trying to aggregate information from these sources should be able to access each one of them in a different way.

The purpose of this project is to develop translation tools for different social annotation systems, collect their data in a common format (expressed using an ontology), and show them through a unique user interface, able to display different annotations (i.e. geo coordinates, dates, tags, etc.) in different ways. Moreover, tests and evaluations should be performed on this aggregator to show how efficient the queries are when performed on-the-fly or from an intermediate knowledge base.

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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: Autistic Children Play Robot
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Title: Autistic Children Play Robot
Description: Within a Polisocial project we will have to implement a robot suitable to play autonomously with autistic children that will interact with it and a game system by gestures.

The thesis will explore some of the aspects of the problem, eventually participating to the production of prototypes to be tested with real users. The thesis gives the possibility to develop a robot with special requirements, and to work with gesture interpretation by using devices such as Kinect or the WII Mote. The work is done in an interdisciplinary group including care givers and designers.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 20 January 2015
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: Robogames

Wiki Page: Automatic Content Generation in Computer Games
Gar.jpg
Title: Automatic Content Generation in Computer Games
Description: The generation of customized game content for each player is an attractive direction to improve the game experience in the next-generation computer games. In this scenario, Machine Learning could play an important role to provide automatically such customized game content. Several projects and theses are available on this topic, please contact us for additional information.

Picture taken from http://gar.eecs.ucf.edu/

References
Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Automatic Differentiation Techniques for Real Time Kalman Filtering
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Title: Evaluation of Automatic Differentiation Techniques for Gauss-Newton based Simultaneous Localization and Mapping
Description: In Gauss-Newton non linear optimization one of the most tedious part is computing Jacobians. At the AIRLab we have developed a framework for non linear Simultaneous Localization and Mapping suitable for different motion models and measurement equations, but any time you need to change something you need to recompute the required Jacobian. Automatic differentiation is a tool for the automatic differentiation of source code either at compiling time or at runtime; we are interested in testing these techniques in the software we have developed and compare their performance with respect to (cumbersome) optimized computation.

Material

Expected outcome: New modules implementations based on automatic differentiation A comparison between the old stuff and new approach

Required skills or skills to be acquired:

  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Automatic generation of domain ontologies
Title: Automatic generation of domain ontologies
Description: This thesis to be developed together with Noustat S.r.l. (see http://www.noustat.it), who are developing research activities directed toward the optimization of knowledge management services, in collaboration with another company operating in this field. This project is aimed at removing the ontology building bottleneck, long and expensive activity that usually requires the direct collaboration of a domain expert. The possibility of automatic building the ontology, starting from a set of textual documents related to a specific domain, is expected to improve the ability to provide the knowledge management service, both by reducing the time-to-application, and by increasing the number of domains that can be covered. For this project, unsupervised learning methods will be applied in sequence, exploiting the topological properties of the ultra-metric spaces that emerge from the taxonomic structure of the concepts present in the texts, and associative methods will extend the concept network to lateral, non-hierarchical relationships.
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Start:
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning

Wiki Page: Barking Robots
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Title: Barking Robots
Description: Aim of this project is the development of a robot that can operate autonomously at exhibitions and malls to attract people to a given location, by showing interesting behaviors and interacting with people.

The robot first exhibition has been at Robotica 2009, within HI-Tech Expo at Fiera di Milano, on November 23-25, 2009. Here, the robot had to go around in an area delimited by a white stripe and contact verbally and with gestures people entering the area, in order to attract them to the booth.

Behaviors and gestures have still to be developed to come to an interesting and robust demo at next Robotica, or at other ehibits (e.g. at the Museo della Scienza of Milan).

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 25 February 2012
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: Behavior recognition from visual data
Gesturelib.jpg
Title: Behavior recognition from visual data
Description: In the literature several approaches have been used to model observed behaviors and these date back to early approaches in animal behavior analysis (Baum and Eagon, 1967)(Colgan, 1978). Nowadays several techniques are used and they can be roughly classified as: State space models, Automata (e.g., Finite State Machines, Agents, etc.), Grammars (e.g., strings, T-Patterns, etc.), Bayeasian models (e.g., Hidden Markov Models), and Dynamic State Variables. The work will leverage on a huge corpus of techniques to devise the most suitable for behavior recognition from visual data. We exclude from the very beginning any deterministic approach being the phenomenon under observation complex and affected by noisy observations. The focus will be mainly of the use of dynamic graphical models (Ghahramani, 1998) and the application of bottom up learning techniques (Stolcke and Omohundro, 1993)(Stolcke and Omohundro, 1994) for model induction.
  • L. E. Baum and J. A. Eagon. An inequality with applications to statistical estimation for probabilistic functions of markov processes and to a model for ecology. Bull. Amer. Math. Soc, 73(73):360–363, 1967.
  • P. W. Colgan. Quantitative Ethology. John Wiley & Sons, New York, 1978.
  • A. Stolcke and S. M. Omohundro. Hidden markov model induction by bayesian model merging. In Stephen Jos é Hanson, Jack D. Cowan, and C. Lee Giles, editors, Advances in Neural Information Processing Systems, volume 5. Morgan Kaufmann, San Mateo, CA, 1993.
  • Zoubin Ghahramani. Learning dynamic bayesian networks. Lecture Notes in Computer Science, 1387:168, 1998.
  • A. Stolcke and S. M. Omohundro. Best-first model merging for hidden markov model induction. Technical Report TR-94-003, 1947 Center Street, Berkeley, CA, 1994.

Material:

  • papers from major journals and conferences
  • kinet SDK for the extraction of body poses

Expected outcome:

  • general framework for the recognition of behaviors from time series
  • toolkit for behavior segmentation and recognition from time series
  • running prototype based on data coming from the Microsoft kinect sensor

Required skills or skills to be acquired:

  • understanding of techniques for behavior recognition
  • background on pattern recognition and stochastic models
  • basic understanding of computer vision
  • C++ programming under Linux or Matlab
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning
Research Topic: None

Wiki Page: BringMeHome
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Title: BringMeHome
Description:
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 30 March 2013
Students: 1 - 2
CFU: 2 - 20
Research Area: Robotics
Research Topic: E-2? - A robot for exhibitions

Wiki Page: Cognitive SLAM
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Title: Cognitive SLAM
Description: We have developed a system that is able to detect, recognize and track objects in an image taken from a low cost robot equipped with a IMU and a low cost camera. The system is capable to detect and recognize objects using a user defined fuzzy tree classifier. However the system performance is heavily dependent on high level feature extraction, such as geometric features. The problem is non trivial due to noisy low cost camera and changes in the light conditions. The aim of this project is to improve the feature extraction and description process, both in performance and quality, possible adding a more complete description or others type of features. The long term aim of the research is to have an autonomuos robot capable to create a semantic map of the envirorment, localize himself , make inference on the map, navigate into the envirorment using the objects as landmarks.

No special skills are required, except basic c and object oriented programming.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: SLAM, Feature Extraction

Wiki Page: Combinatorial optimization based on stochastic relaxation
Stochastic.jpg
Title: Combinatorial optimization based on stochastic relaxation
Description: The project will focus on the study, implementation, comparison and

analysis of different algorithms for the optimization of pseudo-Boolean functions, i.e., functions defined over binary variables with values in R. These functions have been studied a lot in the mathematical programming literature, and different algorithms have been proposed (1). More recently, the same problems have been faced in evolutionary computations, with the use of genetic algorithms, and in particular estimation of distribution algorithms (2,3). Estimation of distribution algorithms are a recent meta-heuristic, where classical crossover and mutation operators used in genetic algorithms are replaced with operators that come from statistics, such as sampling and estimation.

The focus will be on the implementation of a new algorithm able to combine different approaches (estimation and sampling, from one side, and exploitation of prior knowledge about the structure of problem, on the other), together with the comparison of the results with existing techniques that historically appear in different (and often separated) communities. Good coding (C/C++) abilities are required. Since the approach will be based on statistical models, the student is supposed to be comfortable with notions that come from probability and statistics courses. The project could require some extra effort in order to build and consolidate some background in math, especially in Bayesian statistics and MCMC techniques, such as Gibbs and Metropolis samplers (4).

The project can be extended to master thesis, according to interesting and novel directions of research that will emerge in the first part of the work. Possible ideas may concern the proposal of new algorithms able to learn existing dependencies among the variables in the function to be optimized, and exploit them in order to increase the probability to converge to the global optimum.

Picture taken from http://www.ra.cs.uni-tuebingen.de/

Bibliography

  1. Boros, Endre and Boros, Endre and Hammer, Peter L. (2002) Pseudo-boolean optimization. Discrete Applied Mathematics.
  2. Pelikan, Martin; Goldberg, David; Lobo, Fernando (1999), A Survey of Optimization by Building and Using Probabilistic Models, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign.
  3. Larrañga, Pedro; & Lozano, Jose A. (Eds.). Estimation of distribution algorithms: A new tool for evolutionary computation. Kluwer Academic Publishers, Boston, 2002.
  4. Image Analysis, Random Fields Markov Chain Monte Carlo Methods
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Machine Learning
Research Topic: Information Geometry, Stochastic Optimization

Wiki Page: Combining Estimation of Distribution Algorithms and other Evolutionary techniques for combinatorial optimization
Evolve1at300dpi.gif
Title: Combining Estimation of Distribution Algorithms and other Evolutionary techniques for combinatorial optimization
Description: The project will focus on the study, implementation, comparison and analysis of different algorithms for combinatorial optimization using techniques and algorithms proposed in Evolutionary Computation. In particular we are interested in the study of Estimation of Distribution Algorithms (1,2,3,4), a recent meta-heuristic, often presented as an evolution of Genetic Algorithms, where classical crossover and mutation operators, used in genetic algorithms, are replaced with operators that come from statistics, such as sampling and

estimation.

The focus will be on the implementation of new hybrid algorithms able to combine estimation of distribution algorithms with different approaches available in the evolutionary computation literature, such as genetic algorithms and evolutionary strategies, together with other local search techniques. Good coding (C/C++) abilities are required. Some background in combinatorial optimization form the "Fondamenti di Ricerca Operativa" is desirable. The project could require some effort in order to build and consolidate some background in MCMC techniques, such as Gibbs and Metropolis samplers (4). The project could be extended to master thesis, according to interesting and novel directions of research that will emerge in the first part of the work.

Computer vision provides a large number of optimization problems, such as new-view synthesis, image segmentation, panorama stitching and texture restoration, among the others, (6). One common approach in this context is based on the use of binary Markov Random Fields and on the formalization of the optimization problem as the minimum of an energy function expressed as a square-free polynomial, (5). We are interested in the proposal, comparison and evaluation of different Estimation of Distribution Algorithms for solving real world problems that appear in computer vision.

Pictures taken from http://www.genetic-programming.org and (6)

Bibliography

  1. Pelikan, Martin; Goldberg, David; Lobo, Fernando (1999), A Survey of Optimization by Building and Using Probabilistic Models, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign.
  2. Larrañga, Pedro; & Lozano, Jose A. (Eds.). Estimation of distribution algorithms: A new tool for evolutionary computation. Kluwer Academic Publishers, Boston, 2002.
  3. Lozano, J. A.; Larrañga, P.; Inza, I.; & Bengoetxea, E. (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. Springer, 2006.
  4. Pelikan, Martin; Sastry, Kumara; & Cantu-Paz, Erick (Eds.). Scalable optimization via probabilistic modeling: From algorithms to applications. Springer, 2006.
  5. Image Analysis, Random Fields Markov Chain Monte Carlo Methods
  6. Carsten Rother, Vladimir Kolmogorov, Victor Lempitsky, Martin Szummer. Optimizing Binary MRFs via Extended Roof Duality, CVPR 2007
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 10
Research Area: Machine Learning
Research Topic: Evolutionary Computation, Stochastic Optimization

Wiki Page: Comparison of State of the Art Visual Odometry Systems
VisualOdometry.jpg
Title: A Comparison of State of the Art Visual Odometry Systems (Monocular and Stereo)
Description: Visual odometry is the estimation of camera(s) movement from a sequence of images. In case we deal with a single camera system we have Monocular Visual Odometry; in case we have more cameras we have a Stero Visual Odometry. The goal of the thesis is to review the state of the art on in visual odometry, classify existing approaches and compare their implementations (many of the algorithms have online source code available).

Material

Expected outcome:

  • a set of running algorithms performing visual odometry

Required skills or skills to be acquired:

  • computer vision and 3D reconstruction
  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Computer Vision and Image Analysis
Research Topic: None

Wiki Page: Creation of new EEG training by introduction of noise
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Title: Creation of new EEG training by introduction of noise
Description: A Brain-Computer Interface (BCI) must be trained on the individual user in order to be effective. This training phase require recording data in long sessions, which is time consuming and boring for the user. The aim of this project is to develop algorithm to create new training EEG (electroencephalography) data from existing ones, so as to speed up the training phase.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface

Wiki Page: Data Mining in Computer Games
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Title: Data Mining in Computer Games
Description: Today a lot of data can be extracted from popular games. The analysis of such data allow to discover a lot of interesting information about players, the game and the interaction between the game and different type of players.

Several theses and projects are available on this topic and involve different games: TORCS, Unreal Tournament and Quake Live. Please contact us for additional information.

References
Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Designing Living Objects
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Title: Designing Living Objects
Description: The aim of this activity is to investigate how one or more objects in an antropic environment (home, office, hospital) can be designed and implemented to have a character and to move, having nice interactions with people. The work to be done concerns the analysis, definition, design and implementation of at least one of these objects.
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 15 October 2017
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Living Objects

Wiki Page: Detecting patterns in ontology usage
Title: Detecting patterns in ontology usage
Description: When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

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BioSignal Analysis

Analysis of the Olfactory Signal


Title: Computational Intelligence techniques to analyse the olfactory signal acquired by an electronic nose for cancer diagnosis
Description: The electronic nose is an instrument able to detect and recognize odors, that is the volatile substances in the atmosphere or emitted by the analyzed substance. This device can react to a gas substance by providing signals that can be analyzed to classify the input. It is composed of a sensor array (MOS sensors, in our case) and a pattern classification system based on machine learning techniques. Each sensor reacts in a different way to the analyzed substance, providing multidimensional data that can be considered as a unique olfactory blueprint of the analyzed substance. We have already tested the use of the electronic nose as diagnostic tool for lung cancer; boosted from the very satisfactory results that we have achieved by these analysis, we want to investigate the possibility of diagnosing other types of cancer and to improve the current computation intelligence techniques.

The project is done in collaboration with the Istituto dei Tumori, Milano.

Tools and instruments
Matlab
Bibliography 
BLATT R., BONARINI A, CALABRÒ E, DELLA TORRE M, MATTEUCCI M, PASTORINO U. (2008). Pattern Classification Techniques for Early Lung Cancer Diagnosis using an Electronic Nose. In: Frontiers in Artificial Intelligence and Applications. European Conference on Artificial Intelligence - Prestigious Applications of Intetelligent Systems. Patras, Greece. 21-15 luglio 2008. (vol. 178, pp. 693-697). ISBN/ISSN: 978-1-58603-891-5. IOS Press. File:PAIS.pdf
Tutor: Andrea Bonarini (email), Matteo Matteucci (email), Rossella Blatt (email)
Start: Anytime (a new acquisition phase will start in March)
Number of students: 1-2
CFU: 20


Sleep Staging


Title: Development of a computer-assisted CAP (Sleep cyclic alternating pattern) scoring method
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Description: In 1985, Terzano describes for the first time the Cyclic Alternating Pattern [1] during sleep and, nowadays, CAP is widely accepted by the medical community as basic analysis of sleep. The CAP evaluation is of fundamental importance since it represents the mechanism developed by the brain evolution to monitor the inner and outer world and to assure the survival during sleep. However, visual detection of CAP in polisomnography (i.e., the standard procedure) is a slow and time-consuming process. This limiting factor generates the necessity of new computer-assisted scoring methods for fast CAP evaluation. This thesis deals with the development of a Decision Support System for CAP scoring based on features extraction at multi-system level (by statistical and signal analysis) and Pattern Recognition or Machine Learning approaches. This may allow the automatic detection of CAP sleep and could be integrated, through reinforcement learning techniques, with the corrections given by physicians.
Tools and instruments
Matlab, C/C++
Bibliography
Mario Terzano, Liborio Parrino. Atlas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep, Sleep Medicine 2 (2001) 537–553. [2]
Tutor: Matteo Matteucci (email), Martin Mendez (email), Anna Maria Bianchi (email), Mario Terzano (Ospedale di Parma)
Start: Anytime
Number of students: 1-2
CFU: 20


Brain-Computer Interface
Wiki Page: Creation of new EEG training by introduction of noise
Bci arch.png
Title: Creation of new EEG training by introduction of noise
Description: A Brain-Computer Interface (BCI) must be trained on the individual user in order to be effective. This training phase require recording data in long sessions, which is time consuming and boring for the user. The aim of this project is to develop algorithm to create new training EEG (electroencephalography) data from existing ones, so as to speed up the training phase.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface

Wiki Page: Exploratory data analysis by genetic feature extraction
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Title: Exploratory data analysis by genetic feature extraction
Description: Understanding the waves in EEG signals is an hard task and psicologists often need automatic tools to perform this task. In this project we are interested in using a genetic algorithm developed for P300 feature extraction in order to extract useful informations from Error Potentials. The project is a collaboration with the psicology department od Padua University.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface


Machine Learning

Wiki Page: Automatic generation of domain ontologies
Title: Automatic generation of domain ontologies
Description: This thesis to be developed together with Noustat S.r.l. (see http://www.noustat.it), who are developing research activities directed toward the optimization of knowledge management services, in collaboration with another company operating in this field. This project is aimed at removing the ontology building bottleneck, long and expensive activity that usually requires the direct collaboration of a domain expert. The possibility of automatic building the ontology, starting from a set of textual documents related to a specific domain, is expected to improve the ability to provide the knowledge management service, both by reducing the time-to-application, and by increasing the number of domains that can be covered. For this project, unsupervised learning methods will be applied in sequence, exploiting the topological properties of the ultra-metric spaces that emerge from the taxonomic structure of the concepts present in the texts, and associative methods will extend the concept network to lateral, non-hierarchical relationships.
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Start:
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning

Wiki Page: Behavior recognition from visual data
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Title: Behavior recognition from visual data
Description: In the literature several approaches have been used to model observed behaviors and these date back to early approaches in animal behavior analysis (Baum and Eagon, 1967)(Colgan, 1978). Nowadays several techniques are used and they can be roughly classified as: State space models, Automata (e.g., Finite State Machines, Agents, etc.), Grammars (e.g., strings, T-Patterns, etc.), Bayeasian models (e.g., Hidden Markov Models), and Dynamic State Variables. The work will leverage on a huge corpus of techniques to devise the most suitable for behavior recognition from visual data. We exclude from the very beginning any deterministic approach being the phenomenon under observation complex and affected by noisy observations. The focus will be mainly of the use of dynamic graphical models (Ghahramani, 1998) and the application of bottom up learning techniques (Stolcke and Omohundro, 1993)(Stolcke and Omohundro, 1994) for model induction.
  • L. E. Baum and J. A. Eagon. An inequality with applications to statistical estimation for probabilistic functions of markov processes and to a model for ecology. Bull. Amer. Math. Soc, 73(73):360–363, 1967.
  • P. W. Colgan. Quantitative Ethology. John Wiley & Sons, New York, 1978.
  • A. Stolcke and S. M. Omohundro. Hidden markov model induction by bayesian model merging. In Stephen Jos é Hanson, Jack D. Cowan, and C. Lee Giles, editors, Advances in Neural Information Processing Systems, volume 5. Morgan Kaufmann, San Mateo, CA, 1993.
  • Zoubin Ghahramani. Learning dynamic bayesian networks. Lecture Notes in Computer Science, 1387:168, 1998.
  • A. Stolcke and S. M. Omohundro. Best-first model merging for hidden markov model induction. Technical Report TR-94-003, 1947 Center Street, Berkeley, CA, 1994.

Material:

  • papers from major journals and conferences
  • kinet SDK for the extraction of body poses

Expected outcome:

  • general framework for the recognition of behaviors from time series
  • toolkit for behavior segmentation and recognition from time series
  • running prototype based on data coming from the Microsoft kinect sensor

Required skills or skills to be acquired:

  • understanding of techniques for behavior recognition
  • background on pattern recognition and stochastic models
  • basic understanding of computer vision
  • C++ programming under Linux or Matlab
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning
Research Topic: None

Wiki Page: Combinatorial optimization based on stochastic relaxation
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Title: Combinatorial optimization based on stochastic relaxation
Description: The project will focus on the study, implementation, comparison and

analysis of different algorithms for the optimization of pseudo-Boolean functions, i.e., functions defined over binary variables with values in R. These functions have been studied a lot in the mathematical programming literature, and different algorithms have been proposed (1). More recently, the same problems have been faced in evolutionary computations, with the use of genetic algorithms, and in particular estimation of distribution algorithms (2,3). Estimation of distribution algorithms are a recent meta-heuristic, where classical crossover and mutation operators used in genetic algorithms are replaced with operators that come from statistics, such as sampling and estimation.

The focus will be on the implementation of a new algorithm able to combine different approaches (estimation and sampling, from one side, and exploitation of prior knowledge about the structure of problem, on the other), together with the comparison of the results with existing techniques that historically appear in different (and often separated) communities. Good coding (C/C++) abilities are required. Since the approach will be based on statistical models, the student is supposed to be comfortable with notions that come from probability and statistics courses. The project could require some extra effort in order to build and consolidate some background in math, especially in Bayesian statistics and MCMC techniques, such as Gibbs and Metropolis samplers (4).

The project can be extended to master thesis, according to interesting and novel directions of research that will emerge in the first part of the work. Possible ideas may concern the proposal of new algorithms able to learn existing dependencies among the variables in the function to be optimized, and exploit them in order to increase the probability to converge to the global optimum.

Picture taken from http://www.ra.cs.uni-tuebingen.de/

Bibliography

  1. Boros, Endre and Boros, Endre and Hammer, Peter L. (2002) Pseudo-boolean optimization. Discrete Applied Mathematics.
  2. Pelikan, Martin; Goldberg, David; Lobo, Fernando (1999), A Survey of Optimization by Building and Using Probabilistic Models, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign.
  3. Larrañga, Pedro; & Lozano, Jose A. (Eds.). Estimation of distribution algorithms: A new tool for evolutionary computation. Kluwer Academic Publishers, Boston, 2002.
  4. Image Analysis, Random Fields Markov Chain Monte Carlo Methods
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Machine Learning
Research Topic: Information Geometry, Stochastic Optimization

Wiki Page: Combining Estimation of Distribution Algorithms and other Evolutionary techniques for combinatorial optimization
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Title: Combining Estimation of Distribution Algorithms and other Evolutionary techniques for combinatorial optimization
Description: The project will focus on the study, implementation, comparison and analysis of different algorithms for combinatorial optimization using techniques and algorithms proposed in Evolutionary Computation. In particular we are interested in the study of Estimation of Distribution Algorithms (1,2,3,4), a recent meta-heuristic, often presented as an evolution of Genetic Algorithms, where classical crossover and mutation operators, used in genetic algorithms, are replaced with operators that come from statistics, such as sampling and

estimation.

The focus will be on the implementation of new hybrid algorithms able to combine estimation of distribution algorithms with different approaches available in the evolutionary computation literature, such as genetic algorithms and evolutionary strategies, together with other local search techniques. Good coding (C/C++) abilities are required. Some background in combinatorial optimization form the "Fondamenti di Ricerca Operativa" is desirable. The project could require some effort in order to build and consolidate some background in MCMC techniques, such as Gibbs and Metropolis samplers (4). The project could be extended to master thesis, according to interesting and novel directions of research that will emerge in the first part of the work.

Computer vision provides a large number of optimization problems, such as new-view synthesis, image segmentation, panorama stitching and texture restoration, among the others, (6). One common approach in this context is based on the use of binary Markov Random Fields and on the formalization of the optimization problem as the minimum of an energy function expressed as a square-free polynomial, (5). We are interested in the proposal, comparison and evaluation of different Estimation of Distribution Algorithms for solving real world problems that appear in computer vision.

Pictures taken from http://www.genetic-programming.org and (6)

Bibliography

  1. Pelikan, Martin; Goldberg, David; Lobo, Fernando (1999), A Survey of Optimization by Building and Using Probabilistic Models, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign.
  2. Larrañga, Pedro; & Lozano, Jose A. (Eds.). Estimation of distribution algorithms: A new tool for evolutionary computation. Kluwer Academic Publishers, Boston, 2002.
  3. Lozano, J. A.; Larrañga, P.; Inza, I.; & Bengoetxea, E. (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. Springer, 2006.
  4. Pelikan, Martin; Sastry, Kumara; & Cantu-Paz, Erick (Eds.). Scalable optimization via probabilistic modeling: From algorithms to applications. Springer, 2006.
  5. Image Analysis, Random Fields Markov Chain Monte Carlo Methods
  6. Carsten Rother, Vladimir Kolmogorov, Victor Lempitsky, Martin Szummer. Optimizing Binary MRFs via Extended Roof Duality, CVPR 2007
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 10
Research Area: Machine Learning
Research Topic: Evolutionary Computation, Stochastic Optimization

Wiki Page: Information geometry and machine learning
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Title: Information geometry and machine learning
Description: In machine learning, we often introduce probabilistic models to handle uncertainty in the data, and most of the times due to the computational cost, we end up selecting (a priori, or even at run time) a subset of all possible statistical models for the variables that appear in the problem. From a geometrical point of view, we work with a subset (of points) of all possible statistical models, and the choice of the fittest model in out subset can be interpreted as a the point (distribution) minimizing some distance or divergence function w.r.t. the true distribution from which the observed data are sampled. From this perspective, for instance, estimation procedures can be considered as projections on the statistical model and other statistical properties of the model can be understood in geometrical terms. Information Geometry (1,2) can be described as the study of statistical properties of families of probability distributions, i.e., statistical models, by means of differential and Riemannian geometry.

Information Geometry has been recently applied in different fields, both to provide a geometrical interpretation of existing algorithms, and more recently, in some contexts, to propose new techniques to generalize or improve existing approaches. Once the student is familiar with the theory of Information Geometry, the aim of the project is to apply these notions to existing machine learning algorithms.

Possible ideas are the study of a particular model from the point of view of Information Geometry, for example as Hidden Markov Models, Dynamic Bayesian Networks, or Gaussian Processes, to understand if Information Geometry can give useful insights with such models. Other possible direction of research include the use of notions and ideas from Information Geometry, such as the mixed parametrization based on natural and expectation parameters (3) and/or families of divergence functions (2), in order to study model selection from a geometric perspective. For example by exploiting projections and other geometric quantities with "statistical meaning" in a statistical manifold in order to chose/build the model to use for inference purposes.

Since the project has a theoretical flavor, mathematical inclined students are encouraged to apply. The project requires some extra effort in order to build and consolidate some background in math, partially in differential geometry, and especially in probability and statistics.

Bibliography

  1. Shun-ichi Amari, Hiroshi Nagaoka, Methods of Information Geometry, 2000
  2. Shun-ichi Amari, Information geometry of its applications: Convex function and dually flat manifold, Emerging Trends in Visual Computing (Frank Nielsen, ed.), Lecture Notes in Computer Science, vol. 5416, Springer, 2009, pp. 75–102
  3. Shun-ichi Amari, Information geometry on hierarchy of probability distributions, IEEE Transactions on Information Theory 47 (2001), no. 5, 1701–1711.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning
Research Topic: Information Geometry

Wiki Page: LARS and LASSO in non Euclidean Spaces
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Title: LARS and LASSO in non Euclidean Spaces
Description: LASSO (1) and more recently LARS (2) are two algorithms proposed for linear regression tasks. In particular LASSO solves a least-squares (quadratic) optimization problem with a constrain that limits the sum of the absolute value of the coefficients of the regression, while LARS can be considered as a generalization of LASSO, that provides a more computational efficient way to obtain the solution of the regression problem simultaneously for all values of the constraint introduced by LASSO.

One of the common hypothesis in regression analysis is that the noise introduced in order to model the linear relationship between regressors and dependent variable has a Gaussian distribution. A generalization of this hypothesis leads to a more general framework, where the geometry of the regression task is no more Euclidean. In this context different estimation criteria, such as maximum likelihood estimation and other canonical divergence functions do not coincide anymore. The target of the project is to compare the different solutions associated to different criteria, for example in terms of robustness, and propose generalization of LASSO and LARS in non Euclidean contexts.

The project will focus on the understanding of the problem and on the implementation of different algorithms, so (C/C++ or Matlab or R) coding will be required. Since the project has also a theoretical flavor, mathematical inclined students are encouraged to apply. The project may require some extra effort in order to build and consolidate some background in math, especially in probability and statistics.

Picture taken from (2)

Bibliography

  1. Tibshirani, R. (1996), Regression shrinkage and selection via the lasso. J. Royal. Statist. Soc B., Vol. 58, No. 1, pages 267-288
  2. Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani, Least Angle Regression, 2003
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Start: 1 October 2009
Students: 1 - 2
CFU: 20 - 20
Research Area: Machine Learning
Research Topic: Informtion Geometry

Wiki Page: Statistical inference for phylogenetic trees
Toloverview.jpg
Title: Statistical inference for phylogenetic trees
Description: The project will focus on the study, implementation, comparison, and analysis of different statistical inference techniques for phylogenetic trees. Phylogenetic trees (1, 2, 3) are evolutionary trees used to represent the relationships between different species with a common ancestor. Typical inference tasks concern the construction of a tree starting from DNA sequences, involving both the choice of the topology of the tree (i.e., model selection) and the values of the parameters (i.e., model fitting). The focus will be a probabilistic description of the tree, given by the introduction of stochastic

variables associated to both internal nodes and leaves of the tree.

The project will focus on the understanding of the problem and on the implementation of different algorithms, so (C/C++ or Matlab or R) coding will be required. Since the approach will be based on statistical models, the student is supposed to be comfortable with notions that come from probability and statistics courses.

The project is thought to be extended to master thesis, according to interesting and novel directions of research that will emerge in the first part of the work. Possible ideas may concern the proposal and implementation of new algorithms, based on recent approaches to phylogenetic inference available in the literature, as in (3) and (4). In this case the thesis requires some extra effort in order to build and consolidate some background in math in oder to understand some recent literature, especially in (mathematical) statistics and, for example, in the emerging field of algebraic statistics (5).

Other possible novel applications of phylogenetic trees have been proposed in contexts different from biology, as in (6). Malware (malicious software) is software designed to infiltrate a computer without the owner's informed consent. Often malwares are related to previous programs thought evolutionary relationships, i.e., new malwares appear as small mutations of previous softwares. We are interested in the use of techniques from phylogenetic trees to create a taxonomy of real world malwares.

Picture taken from http://www.tolweb.org/tree/ and http://www.blogscienze.com

Bibliography

  1. Felsenstein 2003: Inferring Phylogenies
  2. Semple and Steel 2003: Phylogenetics: The mathematics of phylogenetics
  3. Louis J. Billera, Susan P. Holmes and and Karen Vogtmann Geometry of the space of phylogenetic trees. Advances in Applied Math 27, 733-767 (2001)
  4. Evans, S.N. and Speed, T.P. (1993). Invariants of some probability models used in phylogenetic inference. Annals of Statistics 21, 355-377.
  5. Lior Pachter, Bernd Sturmfels 2005, Algebraic Statistics for Computational Biology.
  6. A. Walenstein, E-Md. Karim, A. Lakhotia, and L. Parida. Malware Phylogeny Generation Using Permutations of Code, Journal in Computer Virology, v1.1, 2005.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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), [[LuigiMalago | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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), [[StefanoZanero | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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)
Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Machine Learning
Research Topic: Information Geometry, Stocastic Optimization, Evolutionary Computation



Title: Reinforcement Learning in Poker
PokerPRLT.png
Description: In this years, Artificial Intelligence research has shifted its attention from fully observable environments such as Chess to more challenging partially observable ones such as Poker.

Up to this moment research in this kind of environments, which can be formalized as Partially Observable Stochastic Games, has been more from a game theoretic point of view, thus focusing on the pursue of optimality and equilibrium, with no attention to payoff maximization, which may be more interesting in many real-world contexts.

On the other hand Reinforcement Learning techniques demonstrated to be successful in solving both fully observable problems, single and multi-agent, and single-agent partially observable ones, while lacking application to the partially observable multi-agent framework.

This research aims at studying the solution of Partially Observable Stochastic Games, analyzing the possibility to combine the Opponent Modeling concept with the well proven Reinforcement Learning solution techniques to solve problems in this framework, adopting Poker as testbed.

Tutor: Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it)
Start: Anytime
Number of students: 1-2
CFU: 20-40



Title: Automatic generation of domain ontologies [[Image:|center|300px]]
Description: This thesis to be developed together with Noustat S.r.l., who are developing research activities directed toward the optimization of knowledge management services, in collaboration with another company operating in this field. This project is aimed at removing the ontology building bottleneck, long and expensive activity that usually requires the direct collaboration of a domain expert. The possibility of automatic building the ontology, starting from a set of textual documents related to a specific domain, is expected to improve the ability to provide the knowledge management service, both by reducing the time-to-application, and by increasing the number of domains that can be covered. For this project, unsupervised learning methods will be applied in sequence, exploiting the topological properties of the ultra-metric spaces that emerge from the taxonomic structure of the concepts present in the texts, and associative methods will extend the concept network to lateral, non-hierarchical relationships.
Tutor: Matteo Matteucci (email), Andrea Bonarini (email)
Start: before November 30th
Number of students: 1-2
CFU: 20


Computational Intelligence and Games

Wiki Page: AI in Racing Games
TORCS2.jpg
Title: AI in Racing Games
Description: This project is focused on TORCS, a state-of-the-art open source racing simulator. From one hand, TORCS represents an ideal bechmark to study Computational Intelligence techniques. On the other hand, Computational Intelligence techniques could be used to improve the game experience in this kind of games. Several projects and theses are available on this topic, please contact us for additional information.

References:

Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Automatic Content Generation in Computer Games
Gar.jpg
Title: Automatic Content Generation in Computer Games
Description: The generation of customized game content for each player is an attractive direction to improve the game experience in the next-generation computer games. In this scenario, Machine Learning could play an important role to provide automatically such customized game content. Several projects and theses are available on this topic, please contact us for additional information.

Picture taken from http://gar.eecs.ucf.edu/

References
Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Data Mining in Computer Games
QLive.png
Title: Data Mining in Computer Games
Description: Today a lot of data can be extracted from popular games. The analysis of such data allow to discover a lot of interesting information about players, the game and the interaction between the game and different type of players.

Several theses and projects are available on this topic and involve different games: TORCS, Unreal Tournament and Quake Live. Please contact us for additional information.

References
Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games

Wiki Page: Human-Like AI in Games
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Title: Human-Like AI in Games
Description: Developing a human-like AI is a challenging and fascinating problem from the point of view of the Artificial Intelligence research. At the same time, it is also a significative prolem for the computer games development: playing against humans is generally more exciting than playing against computers.

Our projects and theses on this topic involve two different games: Unreal Tournament 2004 and TORCS. Please contact us for additional information.

References
Tutor: [[DanieleLoiacono | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Computational Intelligence and Games
Research Topic: Computational Intelligence and Games


Social Software and Semantic Web

Wiki Page: A firefox extension for semantic annotations
Title: A Firefox extension for semantic annotations
Description: Aim of this project is to develop a Firefox extension, to allow a community of users to annotate resources on the Web using a shared RDF vocabulary.

While browsing the Web, a user should be able to visualize the annotations relative to the page they are visiting, and to add new annotations as well.

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: Annotation aggregators from social applications
Title: Annotation aggregators from social applications
Description: Annotations are metadata published about a resource, such as tags in del.icio.us, comments on stumbleupon.com, or twines on Twine.com. One of the main problems of these annotations is that they are not expressed in a standard format: thus, any tool trying to aggregate information from these sources should be able to access each one of them in a different way.

The purpose of this project is to develop translation tools for different social annotation systems, collect their data in a common format (expressed using an ontology), and show them through a unique user interface, able to display different annotations (i.e. geo coordinates, dates, tags, etc.) in different ways. Moreover, tests and evaluations should be performed on this aggregator to show how efficient the queries are when performed on-the-fly or from an intermediate knowledge base.

Tutor: [[DavideEynard | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: Detecting patterns in ontology usage
Title: Detecting patterns in ontology usage
Description: When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
Tutor: [[DavideEynard | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: Extending a search engine with semantic information
Velociraptor.png
Title: Extending a search engine with semantic information
Description: We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.

Aim of this project is to expand a traditional search engine with semantic information, so that also documents containing words related to the ones in the query can be retrieved. Existing thesauri and ontologies can be used, as well as more dynamic and collaborative sources of knowledge such as user tags and wikipedia pages and categories.

Starting points for this work can be the projects "SeQuEx - Semantic Query Expansion" and "Enriching search results with semantic metadata".

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Search

Wiki Page: Mining wikipedia categories
Wikipedia categories.png
Title: Wikipedia category map
Description: Wikipedia articles are organized in a hierarchy of categories, manually assigned by users. This process can be considered a huge effort for the collective categorization of human knowledge; the result is a wide and disordered graph which can provide precious information for a variety of applications (natural language processing, information retrieval, ontology building...).

In the project "Wikipedia Category Map" a tool has been developed to extract the graph of Wikipedia categories, to store it in RDF format and to interactively visualize and explore it. Aim of this project is to analyze the resulting graph for the extraction of semantic relationships; for example it is possible to define metrics of distance between topics in the graph, which can be useful for various purposes in information retrieval.

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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), [[RiccardoTasso | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 7 July 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Tagging

Wiki Page: Social Network Data Extraction from Online Communities
SocialNetworkDataExtraction.png
Title: Social Network Data Extraction From Online Communities
Description: With the growth of the Web and the emergence of online communities, a huge amount of data regarding social relationships is now available, that was unthinkable until a few years ago. The network of connections may unveil precious information about communities structures and dynamics and the spreading of information in the Web.

Aim of this project is to design and develop a software tool to extract this kind of information from a single social network platform (decided by the student). It may be required also some kind of analysis or visual representation of the collected data.

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Social Network Analysis

Wiki Page: Use case design and implementation for semantic annotations
Title: Use case design and implementation for semantic annotation
Description: Semantic annotations offer a variety of possibilities to enhance the user experience while browsing the Web. Aim of this project is to propose one scenario in which their usefulness is exploited for a specific community of users. In detail the project requires to design a simple ontology which describes some kind of domain to annotate resources on the Web and implement an interface to query it and insert assertions inside a semantic store (through SPARQL).

One possible example is the annotation of mp3 files available on the Web. They can be classified in genres or associated to datatype properties, such as rating, title, length and release date... also exploiting data already available in http://musicbrainz.org/

Tutor: [[DavideEynard | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 10
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations

Wiki Page: Wikipedia Page Social Network
Title: Wikipedia Page Social Network
Description: Goal of this project is to study the social network of Wikipedia pages, where two pages are connected if they share at least one main contributor. This social network can be studied to reveal interesting information; for example, it is possible to extract clusters of pages which apparently have nothing in common. A metric of distance between pages in the network can be defined, and compared with other metrics, such as the distance in the category tree or in the hyperlink graph.
Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Social Network Analysis

Wiki Page: Wikipedia Tripartite Graph
Title: Wikipedia Tripartite Graph
Description: When a user edits a Wikipedia page, we can establish a link among her, the page and the categories to which the page belongs. A model to represent this information is a tripartite graph. Aim of this project is to build a tripartite graph from Wikipedia users, pages and categories, and mine the outcome network to extract emergent semantics.
Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 20 - 20
Research Area: Social Software and Semantic Web
Research Topic: Social Network Analysis, Semantic Tagging


Robotics


Title: Robot games
Robowii robot.jpg
Description: The goal of this activity is to develop an interactive game with robots using commercial devices such as the WII Mote (see the Robogames page)

Projects are available in different areas:

  • Design and implementation of the game on one of the available robots and extension of the robot functionalities
  • Design and implementation of the game and a new suitable robot
  • Evaluation of the game with users (in collaboration with Franca Garzotto)

These projects allow to experiment with real mobile robots and real interaction devices.

Parts of these projects can be considered as course projects. These projects can also be extended to cover course projects.

Tutor: Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it)
Start: Anytime
Number of students: 1-2
CFU: 7.5-20




Wiki Page: 3D Scene Understanding
FreeCamera.png
Title: 3D Indoor scene understanding and layout reconstruction for a mobile robot in collaboration with UnimiB
Description: The proposed project aims to reconstruct the 3D structural layout of an indoor environment perceived by a mobile robot. From the sensorial data, the robot should be able to reconstruct a geometrical structure of an indoor environment (e.g., an office).

Methods for indoor layout reconstruction must be significantly more tolerant to missing data than their outdoor counterparts, since environments such as offices and apartments exhibit extremely high levels of clutter, which typically results in heavy occlusions of walls and other structures of interest, large-scale artifacts, noise and missing data. The proposed work will be developed in collaboration with IRALAB, the Robotics Lab of University of Milano Bicocca.

The work will be based on an existing project, Free Your Camera (http://www.ira.disco.unimib.it/research/robotic-perception-research/free-your-camera-3d-indoor-scene-understanding-from-arbitrary-camera-motion/) and will be part of a robotic framework based on with ROS and in development at IRALAB.

Tutor: [[FrancescoAmigoni | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 February 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: Robotics

Wiki Page: Autistic Children Play Robot
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Title: Autistic Children Play Robot
Description: Within a Polisocial project we will have to implement a robot suitable to play autonomously with autistic children that will interact with it and a game system by gestures.

The thesis will explore some of the aspects of the problem, eventually participating to the production of prototypes to be tested with real users. The thesis gives the possibility to develop a robot with special requirements, and to work with gesture interpretation by using devices such as Kinect or the WII Mote. The work is done in an interdisciplinary group including care givers and designers.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 20 January 2015
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: Robogames

Wiki Page: Automatic Differentiation Techniques for Real Time Kalman Filtering
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Title: Evaluation of Automatic Differentiation Techniques for Gauss-Newton based Simultaneous Localization and Mapping
Description: In Gauss-Newton non linear optimization one of the most tedious part is computing Jacobians. At the AIRLab we have developed a framework for non linear Simultaneous Localization and Mapping suitable for different motion models and measurement equations, but any time you need to change something you need to recompute the required Jacobian. Automatic differentiation is a tool for the automatic differentiation of source code either at compiling time or at runtime; we are interested in testing these techniques in the software we have developed and compare their performance with respect to (cumbersome) optimized computation.

Material

Expected outcome: New modules implementations based on automatic differentiation A comparison between the old stuff and new approach

Required skills or skills to be acquired:

  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Barking Robots
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Title: Barking Robots
Description: Aim of this project is the development of a robot that can operate autonomously at exhibitions and malls to attract people to a given location, by showing interesting behaviors and interacting with people.

The robot first exhibition has been at Robotica 2009, within HI-Tech Expo at Fiera di Milano, on November 23-25, 2009. Here, the robot had to go around in an area delimited by a white stripe and contact verbally and with gestures people entering the area, in order to attract them to the booth.

Behaviors and gestures have still to be developed to come to an interesting and robust demo at next Robotica, or at other ehibits (e.g. at the Museo della Scienza of Milan).

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 25 February 2012
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: BringMeHome
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Title: BringMeHome
Description:
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 30 March 2013
Students: 1 - 2
CFU: 2 - 20
Research Area: Robotics
Research Topic: E-2? - A robot for exhibitions

Wiki Page: Cognitive SLAM
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Title: Cognitive SLAM
Description: We have developed a system that is able to detect, recognize and track objects in an image taken from a low cost robot equipped with a IMU and a low cost camera. The system is capable to detect and recognize objects using a user defined fuzzy tree classifier. However the system performance is heavily dependent on high level feature extraction, such as geometric features. The problem is non trivial due to noisy low cost camera and changes in the light conditions. The aim of this project is to improve the feature extraction and description process, both in performance and quality, possible adding a more complete description or others type of features. The long term aim of the research is to have an autonomuos robot capable to create a semantic map of the envirorment, localize himself , make inference on the map, navigate into the envirorment using the objects as landmarks.

No special skills are required, except basic c and object oriented programming.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: SLAM, Feature Extraction

Wiki Page: Designing Living Objects
EmotionalTrashBin.jpg
Title: Designing Living Objects
Description: The aim of this activity is to investigate how one or more objects in an antropic environment (home, office, hospital) can be designed and implemented to have a character and to move, having nice interactions with people. The work to be done concerns the analysis, definition, design and implementation of at least one of these objects.
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 15 October 2017
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Living Objects

Wiki Page: Extended Kalman Filtering on Manifolds
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Title: Extended Kalman Filtering on Manifolds
Description: Extended Kalman filtering is a well known technique for the estimation of the state of a dynamical system also used in robotics for localization and mapping. However in the basic formulation it assumes all variables to live in an Euclidean space while some components may span over the non-Euclidean 2D or 3D rotation group SO(2) or SO(3). It is thus possible to write tha Extended Kalman filter to operate on Lie Groups to take into account the presence of manifolds (http://www.ethaneade.org/latex2html/lie/lie.html). We are interestend in investigation this further applying it to the EKF-SLAM framework we have developed.

Material:

  • papers about Manifold based optimization and space representations
  • C++ framework for EKF-SLAM

Expected outcome:

  • An extended Kalman filter which uses this new representation

Required skills or skills to be acquired:

  • Good mathematical background
  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: LCM middleware on embedded platform
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Title: LCM middleware on embedded platform
Description: We are developing a framework for rapid prototyping of low-cost robotic systems. To fasten robot design and building, and to make software and hardware reuse easier, a modular architecture is mandatory.

In a context of smart modules that have to cooperate by exchanging data to reach their common goal, the communication protocol and middleware are core components. This project is about the middleware component, a publish/subscribe system that takes care of managing topics, publisher and subscribers, and of marshaling data before sending it. This project aims at porting the LCM marshaling and middleware library, developed at MIT and used in the Grand Challenge competition, to embedded systems, in order to exploit the existing LCM tools and to be compliant with an existing and efficient technology.

The project consists in:

  • stripping non necessary features of LCM to match the constraints of an embedded system and of the communication protocol
  • adding necessary features, like the concept of deadline (and priority as a consequence), that are mandatory for a real time distributed system
  • building a gateway, on an embedded platform, that acts as gateway between the standard-LCM world and the embededd-LCM network

The projects has to be developed in ANSI C, and experience with embedded platforms is a plus.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2011
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: MoonSLAM Reengineering
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Title: Reengineering of a flexible framework for simultaneous localization and mapping
Description: In the last three years a general framework for the implementation of EKF-SLAM algorithm has been developed at the AIRLab. After several improvements it is now time to redesign it based on the experience cumulated. The goal is to have an international reference framework for the development of EKF based SLAM algorithms with multiple sensors (e.g., lasers, odometers, inertial measurement ) and different motion models (e.g., free 6DoF motion, planar motion, ackerman kinematic, and do on). The basic idea is to implement it by using C++ templates, numerically stable techniques for Kalman filtering and investigation the use of automatic differentiation. It should be possible to seamlessly exchange motion model and sensor model without having to write code beside the motion model and the measurement equation.

Material

  • lots of theoretical background and material
  • an existing (and working) C++ implementation of the framework

Expected outcome:

  • a C++ library for the implementation of generic EKF-SLAM algorithms

Required skills:

  • Experienced C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Odometric system for robots based on laser mice
Calibration.png
Title: Odometric system for robots based on laser mice
Description: We developed an odometric system for robots by combining the reading of several laser mice. The system consists of a master PIC-based board and several slave boards where the sensors employed in optical mice are located. The readings are collected on the PIC and sent on the serial port to a PC which elaborates and combines the x and y readings in order to obtain a x,y,theta estimation of the movement of the robot.

The aim of the project is first to improve the current design of the PIC-based board, and realize a new working prototype, and then to implement and evaluate different algorithms able to estimate more precisely the x,y and theta odometric data from the mice readings. Experience with PIC-based systems and some experience with electronics circuits is a plus. Students are supposed to redesign the electronic board, improve the firmware of the PIC, and work on the algorithm that estimates the robot position on the PC. It would be also interesting to evaluate the possibility to embed the optimization and estimation algorithms in the firmware of the PIC in order to produce a stand-alone device.

Ask the tutors of the project for extra material, such as data-sheets and other documentation.

Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: R2P IMU firmware development
R2P IMU.png
Title: Embedded Inertial Measurement Unit for Unmanned Aerial Vehihcles
Description: We have developed the electronics of an Inertial Measurement Unit based on an ARM microcontroller to be integrated on an autonomous embedded aerial platform. The IMU has already some attitude heading reference system (AHRS) code implemented, but we are interested in:
  • implementing embedded algorithms for the estimation of the IMU attitude to be compared with the actual one (e.g., Kalman filter, DCM, Madgwick, etc.)
  • developing a, easy to use, procedure for the calibration of IMU parameters
  • making a comparison with commercial units using a robot arm as testbed
  • validate the accuracy of the IMU on a flying platform
  • integrate the measurements from a GPS to reduce drift and provide accurate positiong (this will make it definitely a MS thesis)

Material

  • electronic board and eclipse based C development toolkit for ARM processors
  • papers describing the algorithms we are interested in implementing

Expected outcome:

  • few different AHRS algorithms with comparative results
  • user-friendly procedure to calibrate the IMU
  • a sistem which integrated IMU and GPS to provide accurate positioning

Required skills or skills to be acquired:

  • C programming on ARM microcontroller
  • background on kalman filtering and attitude estimation
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2015
Students: 1 - 2
CFU: 2 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: ROS navigation local planner
Title: ROS_navigation_local_planner
Description: The project will be focused on the implementation of a planner and tracking algorithms for Ackermann vehicles
Tutor: {{EmailViz|1=[[:User:MatteoMatteucci}}, MatteoMatteucci (), [[]] | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: October 2017
Students: 1 - 3
CFU: 2 - 20
Research Area: Robotics
Research Topic: Local Planner

Wiki Page: Robocentric MoonSLAM
RobocentricSLAM.gif
Title: Robocentric implementation in the MoonSLAM framework
Description: Simultaneous Localization and Mapping (SLAM) is one of the basic functionalities required from an autonomous robot. In the past we have developed a framework for building SLAM algorithm based on the use of the Extended Kalman Filter and vision sensors. The actual implementation of the EKF SLAM in the framework developed uses a world-centric approach, but from the literature it is known that a robocentric approach can provide higher performances on small maps. We would like to have both implementation to compare the results in two scenarios: pure visual odometry, conditional independent submapping.

Material

  • A framework for multisensor SLAM using the world centric approach
  • Papers and report about robocentric slam

Expected outcome:

  • a fully functional robocentric version of the MoonSLAM framework

Required skills or skills to be acquired:

  • Basic background in computer vision
  • Background in Kalman filtering
  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Robot Games
Spykeecontorri.jpg
Title: Robot Games
Description: Projects may include the design of an interactive game on an existing or a new robot, and its evaluation. These projects allow to experiment with real mobile robots and interaction devices. Some games may be designed for disabled children. The project can be considered a MS thesis if it can produce a new game and, possibly, a new robot, and includes adapting the behavior of the robot to the player.
Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start:
Students: 1 - 2
CFU: 2 - 20
Research Area: Robotics
Research Topic: Robogames

Wiki Page: Scan Matching Odometry and Multisensor SLAM
ScanMatching.jpg
Title: Scan Matching Odometry and Multisensor SLAM
Description: Starting from some C/C++ code for laser scan alignment and the covariance information associated to the matching, we are interested in the development of a library for the matching and fusion of laser scans under the ROS (www.ros.org) environment. From this we are interested in the development of an odometric system based on laser scan matching and in a Simultaneous Localization and Mapping system integrating scan matching with visual SLAM. The result is a complete navigation system that fuses laser and visual information to build consisten maps in an EKF-based environment.

Material:

  • a MS thesis which describes the scan matching algorithms
  • a BS thesis which implements a prototype of the system

Expected outcome:

  • a complete system that build maps integrating laser scan and visual informtion

Required skills or skills to be acquired:

  • Background on Kalman filtering
  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Self calibration of multiple odometric sensors
HandEye.jpg
Title: Self calibration of multiple odometric sensors mounted on the same platform
Description: An odometric sensor measures the path followed by a robot in an incremental way (e.g., wheel mounted encoders, visual odometry, scan matching based odometry, etc.) . Having several odometry sensors mounted on the same platform can significantly improve the accuracy and robustness of the overall system but requires proper calibration of relative positioning and possible biases. We are interested in the development of techniques for the self calibration of a multi sensor based odometry sensor. These techniques could be inspired by classical non-linear optimization techniques used in the hand and eye problem but they could use techniques from Simultaneous Localization and Mapping. According to the setup, some information on the real position of the system may exists (i.e., external tracking system or GPS); the approach should be able to use this information as well.

Material:

  • datasets with real data
  • a few odometric system implementations
  • C++ libraries for non linear optimization

Expected outcome:

  • software for the self calibration of a set of odometry systems mounted on the same robot

Required skills or skills to be acquired:

  • C++ programming under Linux
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2012
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: None

Wiki Page: Simulation in robotics using UDK USARSIM
P3AT.png
Title: Simulation_in_robotics_using_UDK_USARSIM
Description: USARSim (Unified System for Automation and Robot Simulation) is a high-fidelity simulation of robots and environments based on UDK (Unreal Development Kit), the free edition of the Unreal Engine 3 game engine. It is intended as a research tool and is the basis for the RoboCup Rescue Virtual Robot Competition.

The proposed project is aimed at extending USARSim along two directions:

  • Development of a tool for automatically generating realistic 3D worlds for robot testing. This task involves work on 3D game modelling and development using the UDK engine.
  • Create test arenas and perform experiment in USARSim. Simulation tools as USARSim are powerful tools for robotics, but in order to consider the results obtained in a virtual environment also valid in the real case, simulated environments must be validated through experiments performed both in virtually and with real robots.

Results will be included in the USARSim project and used by the RoboCup community.

Tutor: [[FrancescoAmigoni | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 April 2014
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: RoboCup Rescue

Wiki Page: Soccer Robots
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Title: Soccer Robots
Description: Projects are available in different areas:
  • Implementation of mechanical and electronical parts of the robots for the management of the ball and kicking
  • Design of robot behaviors (fuzzy systems)
  • Coordination of robots
  • New sensors


These projects allow to experiment with real mobile robots. Participation to the championships is a unique experience (2000 people, with 800 robots playing all sort of games...)

The project can be turned into a thesis by facing different problems in depth.

Tutor: [[MarcelloRestelli | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 January 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development

Wiki Page: Stability and motion control of a balancing robot
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Title: Stability and motion control of a balancing robot
Description: This project is focused on the control of both stability and motion of TiltOne, a balancing robot.

TiltOne is a robot with only two wheels that can stand in vertical position following an unstable equilibrium point. The control is applied by commanding an amount of torque to the wheels, allowing the robot to mantain it's gravity center vertical aligned to the wheel axis.

The aim of the project proposal is to implement and compare different control solutions, based on classical approach (as PID and LQR control) and Machine Learning approach (as Reinforcement Learning control policies), that allow the robot to move following a given trajectory at a given speed.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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), [[MartinoMigliavacca | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 March 2010
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development

… further results