Difference between revisions of "2nd Level Course Projects"

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(New page: Here you can find a list of project proposals for the courses of "Laboratorio di Intelligenza Artificiale e Robotica" (5 CFU for each student) and "Soft Computing" (1 CFU for each student)...)
 
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Here you can find a list of project proposals for the courses of "Laboratorio di Intelligenza Artificiale e Robotica" (5 CFU for each student) and "Soft Computing" (1 CFU for each student).  See [[Project Proposals]] for other kinds of projects and theses.
 
Here you can find a list of project proposals for the courses of "Laboratorio di Intelligenza Artificiale e Robotica" (5 CFU for each student) and "Soft Computing" (1 CFU for each student).  See [[Project Proposals]] for other kinds of projects and theses.
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Revision as of 12:25, 10 November 2009

Here you can find a list of project proposals for the courses of "Laboratorio di Intelligenza Artificiale e Robotica" (5 CFU for each student) and "Soft Computing" (1 CFU for each student). See Project Proposals for other kinds of projects and theses.

Machine Learning

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
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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
Manifold.jpg
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.
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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
Lasso.jpg
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.
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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


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
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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
UT2004.png
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
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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.

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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.

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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".

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Start:
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Search
Wiki Page: Facebook automatic list suggestion
Facebook-app.png
Title: Facebook Automatic List Suggestion
Description: In Facebook each user can create lists of friends (for example: "high school","university","tennis") to better filter information and manage privacy.

Goal of this project is to develop a Facebook application to analyze a user's network of friends and automatically detect groups to suggest lists.

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Start:
Students: 1 - 2
CFU: 5 - 10
Research Area: Social Software and Semantic Web
Research Topic: Social Network Analysis
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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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


Robotics

Wiki Page: BringMeHome
E2LateralHeadCutSmall.JPG
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: CAN Bus bootloader for STM32 microcontrollers
STM32-H103-1.jpg
Title: CAN Bus bootloader for STM32 microcontrollers
Description: JOINT PROJECT with the Embedded Systems group (contact: Patrick Bellasi http://home.dei.polimi.it/bellasi/)

In order to speed up the development and the maintenance of embedded applications, a way to update the firmware on a microcontroller without the need of connecting cables or programmers can be very handy. We are developing a framework for rapid prototyping of low-cost robots, with smart devices that exchange data on a CAN bus network. The CAN bus bootloader is one of the components we need for this project, enabling remote firmware upgrades of all the devices connected to the CAN network.

This project aims to develop a CAN bus bootloader for STM32 ARM Cortex-M3 microcontrollers, and eventually for other architectures.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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), [[MartinoMigliavacca | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 March 2012
Students: 1 - 2
CFU: 2 - 5
Research Area: Robotics
Research Topic: Robot development
Wiki Page: Cognitive SLAM
C SLAM Recognition2.png
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: Electromagnetic kicker for middle-size RoboCup soccer robots
Kicker.jpg
Title: Electromagnetic kicker for middle-size RoboCup soccer robots
Description: The Milan RoboCup Team, a team of soccer robots that play in the Middle Size league of RoboCup (1) employs as kicker an electromagnetic device entirely designed within the AIRLab with external collaborations such as the Energetic department at Politecnico di Milano and the Electronics section at DEI. Basically, the device consists of a solenoid, a capacitor and a PIC-based board that controls (through an external integrated circuit) the charge of the capacitor at 400V (using the 24V batteries of the robot) and the generation of the magnetic field in the solenoid. The magnetic field accelerates a metallic cylinder that hits the soccer ball.

The aim of the project is to design, implement, test, and evaluate a new version of the device. While the charge phase, implemented by an ad-hoc IC controlled by the PIC, is quite efficient, some work has to be done in order to design a new solenoid and improve the way the PIC implements a sort of modulation of strength of the shoot, in order to implement small passages between robots. The final purpose is to improve the efficiency of the system, with the aim of minimize the energy consumed and maximize the energy transmitted to the ball, in order to obtain more powerful shots.

The first part of the project is focused on some theoretical aspects in order to understand the current design and evaluate how to improve it, while the second phase will be focused on the implementation and test of a new prototype of the kicking device. Experience with PIC-based systems is a plus, but not required, while some experience with electronics circuits is highly recommended. Students are supposed to work in the lab following a set of safety guidelines and rules with circuits at 400V, with 10A pick current during charge phase, and even more during shots. Student from electronics engineering are really welcomed to choose this project.

  1. http://www.er.ams.eng.osaka-u.ac.jp/robocup-mid/index.cgi
Tutor: [[LuigiMalago | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 5
Research Area: Robotics
Research Topic: Milan Robocup Team
Wiki Page: Embedded registers view plug-in for Eclipse
STM32-H103-1.jpg
Title: Embedded registers view plug-in for Eclipse
Description: JOINT PROJECT with the Embedded Systems group (contact: Patrick Bellasi http://home.dei.polimi.it/bellasi/)

When developing embedded applications it is frequently needed to look at *hardware register content* in order to *debug the code*. All commercial development suites offer register views that show their contents as well as the meaning of each bit. Open source development solutions currently lack this feature, meaning that you have to look to the correct memory location and map the content to the corresponding register bits manually. This seems to be one of the most limiting issues when developing embedded application using open source solutions.

This project aims to fill this gap, developing an Eclipse plug-in that shows the register contents in a tree viewer, like most commercial suites do.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 30 May 2011
Students: 1 - 2
CFU: 2 - 5
Research Area: Robotics
Research Topic: Robot development
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: 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: Scripting language on embedded platforms
STM32-H103-1.jpg
Title: Scripting language on embedded platforms
Description: JOINT PROJECT with the Embedded Systems group (contact: Patrick Bellasi http://home.dei.polimi.it/bellasi/)

When developing embedded applications it is common the need to test some algorithm in some fast way, without to re-program the whole firmware every time. PAWN (http://www.compuphase.com/pawn/) is a *simple and lightweight scripting language with a C-like syntax*. Execution speed, stability, simplicity and a small footprint were essential design criteria for both the language and the abstract machine, making PAWN suitable for embedded applications.

This project aims to port the abstract machine to ARM Cortex-M3 microcontrollers, add a set of functions to interface with the underlying hardware peripherals and then to embed it as ChibiOS/RT (http://www.chibios.org) thread.

Tutor: [[AndreaBonarini | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 30 May 2011
Students: 1 - 2
CFU: 2 - 5
Research Area: Robotics
Research Topic: Robot development
Wiki Page: Soccer Robots
RIeRO.jpg
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
Proposta tiltone.png
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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Start: 1 March 2010
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Robot development



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