Difference between revisions of "Master Level Course Projects"

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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.
  
==== Evolutionary Optimization and Stochastic Optimization ====
 
  
{{Project template
 
|title=Combinatorial optimization based on stochastic relaxation
 
|tutor=[[User:MatteoMatteucci|Matteo Matteucci]] ([mailto:matteucc-AT-elet-DOT-polimi-DOT-it]), [[User:LuigiMalago|Luigi Malagò]] ([mailto:malago-AT-elet-DOT-polimi-DOT-it email])
 
|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 existing algorithms 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.
 
  
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
 
 
 
|start=Anytime
 
|number=1-2
 
|cfu=20-40
 
|image=stochastic.jpg}}
 
 
 
==== Evolutionary Computation ====
 
 
{{Project template
 
|title=Combining Estimation of Distribution Algorithms and other Evolutionary techniques for combinatorial optimization
 
|tutor=[[User:MatteoMatteucci|Matteo Matteucci]] ([mailto:matteucc-AT-elet-DOT-polimi-DOT-it]), [[User:LuigiMalago|Luigi Malagò]] ([mailto:malago-AT-elet-DOT-polimi-DOT-it email])
 
|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.
 
 
Picture taken from http://www.genetic-programming.org
 
 
;Bibliography
 
*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.
 
 
 
|start=Anytime
 
|number=1-2
 
|cfu=5-10
 
|image=genetic.jpg}}
 
 
 
===== Sleep Staging =====
 
 
{{Project template
 
|title=Development of a computer-assisted CAP (Sleep cyclic alternating pattern) scoring method
 
|tutor=[[User:MatteoMatteucci|Matteo Matteucci]] ([mailto:matteucc%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email]), Martin Mendez ([mailto:martin.mendez@polimi.it email]), Anna Maria Bianchi ([mailto:annamaria.bianchi@polimi.it email]), Mario Terzano (Ospedale di Parma)
 
|description=In 1985, Terzano describes for the first time the Cyclic Alternating Pattern [http://en.wikipedia.org/wiki/Cyclical_alternating_pattern] 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. [http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6W6N-44DY2B4-8&_user=2620285&_coverDate=11%2F30%2F2001&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000058180&_version=1&_urlVersion=0&_userid=2620285&md5=aa61a060d005f23f6afed5c1fc2f1126]
 
|start=Anytime
 
|number=1-2
 
|cfu=5-20
 
|image=CAP_Sleep_Staging.jpg}}
 
 
<!--==== Affective Computing ====
 
-->
 
<!--==== Agents, Multiagent Systems, Agencies ====
 
-->
 
 
==== BioSignal Analysis ====
 
==== BioSignal Analysis ====
  
Line 107: Line 42:
 
|cfu=5-20
 
|cfu=5-20
 
|image=LURCH_wheelchair.jpg}}
 
|image=LURCH_wheelchair.jpg}}
 
{{Project template
 
|title=Online automatic tuning of the number of repetitions in a P300-based BCI
 
|tutor=[[User:MatteoMatteucci|Matteo Matteucci]] ([mailto:matteucc%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email]), [[User:BernardoDalSeno|Bernardo Dal Seno]] ([mailto:dalseno%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email])
 
|description=In a [http://en.wikipedia.org/wiki/P300_(Neuroscience) P300]-based [[Brain-Computer_Interface|BCI]], (visual) stimuli are presented to the user, and the intention of the user is recognized when a P300 potential is recognized in response of the desired stimulus.  In order to improve accuracy, many stimulation rounds are usually performed before making a decision.  The exact number of repetitions depends on the user and the goodness of the classifier, but it is usually fixed a-priori.  The aim of this project is to adapt the number of repetitions to changing conditions, so as to achieve the maximum accuracy with the minimum time.
 
Depending on the effort the student is willing to put into it, the project can grow to a full experimental thesis.
 
 
;Tools and instruments
 
:C++, [http://www.bci2000.org/ BCI2000]
 
 
;Bibliography
 
: E. Donchin, K.M. Spencer, R. Wijesinghe. ''The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface'' [http://www.cs.cmu.edu/~tanja/BCI/P300Speed_2000.pdf]
 
|start=Anytime
 
|number=1
 
|cfu=5-20
 
|image=B_p300_speller.jpg}}
 
  
 
{{Project template
 
{{Project template
Line 280: Line 199:
 
}}
 
}}
  
<!--==== E-Science ====
 
-->
 
==== Machine Learning ====
 
  
 
{{Project template
 
{{Project template
|title=Statistical inference for phylogenetic trees
+
|title=humanoid vision
|tutor=[[User:MatteoMatteucci|Matteo Matteucci]] ([mailto:matteucc-AT-elet-DOT-polimi-DOT-it]), [[User:LuigiMalago|Luigi Malagò]] ([mailto:malago-AT-elet-DOT-polimi-DOT-it email])
+
|tutor=[[User:Giuseppina Gini|Giuseppina Gini]] ([mailto:gini%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email])
|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 task 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.
+
|description=Our goal is to develop vision capabilities for a humanoiud robot. In particular:
 +
* NEURAL-BASED VISION SYSTEM - In this project we experiment different models of the neural structure of the visual cortex. In particular we collect couples of images with different fixation point and we reconstruct disparity, depth, shape recognition. A stereo disparity map is already available.
 +
* RECOGNITION OF HAND MOTIONS - Develop a system able to recognize the hand gestures from images of people. Use this for robot interfacing.
 +
* SEMANTIC MODELLING OF ACTIONS - Construct a semantic representation of actions to be matched against the data obtained from video/movements analysis.
  
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.
 
  
Picture taken from http://www.tolweb.org/tree/
+
|start= Anytime
 +
|number=1-3
 +
|cfu=2.5-15
 +
|image=vision.jpg
 +
}}
  
;Bibliography
+
==== E-Science ====
*[1] Felsenstein 2003: Inferring Phylogenies
+
{{Project template
*[2] Semple and Steel 2003: Phylogenetics: The mathematics of phylogenetics
+
|title=Knowledge discovery in life sciences
*[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)
+
|tutor=[[User:Gini Giuseppina|Gini Giuseppina]] ([mailto:gini%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email])
 +
|description=The goal of those projects is to develop methods and applications in the broad area of life sciences applications. Basic knowledge of chemistry and biology is useful.
 +
* DATA MINING FOR RULE INDUCTION - The project is about analysing large data sets to discover correlations between substructures and properties. CDK and WEKA are possible software to use.
 +
* IReNNS: LEARNING FROM STRUCTURES  - This project will develop IReNNS, a recurrent neural net package, and develop new applications.
 +
* REC analysis in WEKA - The project is about theory and the implementation in Java of REC diagrams. A Matlab tool is available at http://www.cs.rpi.edu/~bij2/rec.html.
 +
* HOW TO TEACH SCIENCE - Propose a web site to teach University students a scientific topic using active participation and virtual experimentation.
 +
* CAUSAL REASONING - In this project we will develop the theory of causality proposed by Pearl and apply it to examples in biological sciences.
 +
Other topics coming soon.
  
|start=Anytime
+
|start= Anytime
|number=1-2
+
|number=2-3
|cfu=20-40
+
|cfu=5-20
|image=toloverview.jpg}}
+
|image=life.jpg
 +
}}
 +
 
 +
 
 +
==== Machine Learning ====
 +
 
 +
{{#ask: [[Category:ProjectProposal]]
 +
[[PrjResArea::Machine Learning]]
 +
[[PrjLevel::Ms]]
 +
[[PrjType::Course]] |
 +
?PrjTitle |
 +
?PrjImage |
 +
?PrjDescription |
 +
?PrjTutor |
 +
?PrjStarts |
 +
?PrjStudMin |
 +
?PrjStudMax |
 +
?PrjCFUMin |
 +
?PrjCFUMax |
 +
?PrjResArea |
 +
?PrjResTopic |
 +
format = template |
 +
template = Template:ProjectProposalViz
 +
}}
  
 
{{Project template
 
{{Project template
Line 313: Line 265:
 
|image=keepaway.gif}}
 
|image=keepaway.gif}}
  
{{Project template
+
==== Computational Intelligence and Games ====
|title= Learning API for TORCS
+
{{#ask: [[Category:ProjectProposal]]
|tutor= Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
+
[[PrjResTopic::Computational Intelligence and Games]]
|description=[http://torcs.sourceforge.net/ TORCS] is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques. The goal of this project is to extend the existing C++ API (available [http://cig.dei.polimi.it/ here]) to simplify the development of controller using a learning framework.
+
[[PrjLevel::Ms]]
Such an extension can be partially developed by porting an existing Java API for TORCS that already provides a lot of functionalities for machine learning approaches.
+
[[PrjType::Course]] |
|start=Anytime
+
?PrjTitle |
|number=1 to 2
+
?PrjImage |
|cfu=5 to 12.5
+
?PrjDescription |
|image=TORCS.jpg}}
+
?PrjTutor |
 +
?PrjStarts |
 +
?PrjStudMin |
 +
?PrjStudMax |
 +
?PrjCFUMin |
 +
?PrjCFUMax |
 +
?PrjResArea |
 +
?PrjResTopic |
 +
format = template |
 +
template = Template:ProjectProposalViz
 +
}}
  
{{Project template
+
==== Social Software and Semantic Web ====
|title= EyeBot
+
|tutor= Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it), Alessandro Giusti (giusti-AT-elet-DOT-polimi-DOT-it), and Pierluigi Taddei (taddei-AT-elet-DOT-polimi-DOT-it)
+
|description=[http://torcs.sourceforge.net/ TORCS] is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques. So far, the controller developed for TORCS used as input only information extracted directly from the state of the game. The goal of this project is to extend the existing controller API (see [http://cig.dei.polimi.it/ here]) to use the visual information (e.g. the screenshots of the game) as input to the controllers. A successfull project will include both the development of the API and some basic imaga preprocessing to extract information from the images.
+
{{#ask: [[Category:ProjectProposal]]
|start=Anytime
+
[[PrjLevel::Bs]]
|number=1 to 2
+
[[PrjType::Course]]
|cfu=5 to 20
+
[[PrjResArea::Social Software and Semantic Web]] |
|image=TORCS2.jpg}}
+
?PrjTitle |
 +
?PrjImage |
 +
?PrjDescription |
 +
?PrjTutor |
 +
?PrjStarts |
 +
?PrjStudMin |
 +
?PrjStudMax |
 +
?PrjCFUMin |
 +
?PrjCFUMax |
 +
?PrjResArea |
 +
?PrjResTopic |
 +
format = template |
 +
template = Template:ProjectProposalViz
 +
}}
  
{{Project template
 
|title= SmarTrack
 
|tutor= Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
 
|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.
 
The goal of this project is to apply machine learning techniques for the generation of customized tracks in
 
[http://torcs.sourceforge.net/ TORCS], a state-of-the-art open source racing simulator. The project include different activities: the automatic generation of tracks, the section of relevant features to characterize a track and the analysis of an interest measure. 
 
|start=Anytime
 
|number=1 to 2
 
|cfu=5 to 20
 
|image=TORCS3.jpg}}
 
 
{{Project template
 
|title= TORCS competition
 
|tutor= Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
 
|description=[http://torcs.sourceforge.net/ TORCS] is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques.
 
The goal of this project is to apply any machine learning technique to develop a successfull controller following the competition rules (available [http://cig.dei.polimi.it/?page_id=67 here])
 
|start=Anytime
 
|number=1
 
|cfu=5
 
|image=TORCS.jpg}}
 
 
<!--==== Ontologies and Semantic Web ====
 
-->
 
 
<!--==== Philosophy of Artificial Intelligence ====
 
<!--==== Philosophy of Artificial Intelligence ====
 
-->
 
-->
 +
 
==== Robotics ====
 
==== Robotics ====
  
{{Project template
+
{{#ask: [[Category:ProjectProposal]]
|title= Robot games
+
[[PrjResArea::Robotics]]
|tutor= Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it)
+
[[PrjLevel::Ms]]
|description=The goal of this activity is to develop an interactive game with robots using commercial devices such as the WII Mote (see the [http://airwiki.elet.polimi.it/mediawiki/index.php/Robogames Robogames page]
+
[[PrjType::Course]] |
Projects are available in different areas:
+
?PrjTitle |
* Design and implementation of the game on one of the available robots
+
?PrjImage |
* Design of the game and a new suitable robot
+
?PrjDescription |
* Implementation/setting of a suitable robot
+
?PrjTutor |
* Evaluation of the game with users (in collaboration with [http://www.elet.polimi.it/people/garzotto Franca Garzotto])
+
?PrjStarts |
 
+
?PrjStudMin |
These projects allow to experiment with real mobile robots and real interaction devices.
+
?PrjStudMax |
 
+
?PrjCFUMin |
The project can be turned into a thesis by producing a new game and robot.
+
?PrjCFUMax |
|start=Anytime
+
?PrjResArea |
|number=1-2
+
?PrjResTopic |
|cfu=5-12.5
+
format = template |
|image=Robowii_robot.jpg}}
+
template = Template:ProjectProposalViz
 
+
}}
{{Project template
+
|title= Robocup: soccer robots
+
|tutor= Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it), Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it)
+
|description=The goal of this activity is to finalize the team of robots that will participate to the robocup world championship in Graz next summer (see the [http://www.robocup.org Robocup page] and the [http://robocup.elet.polimi.it MRT Team page]) 
+
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.
+
|start=Anytime
+
|number=1-2
+
|cfu=5-12.5
+
|image=RIeRO.jpg}}
+
  
  
Line 437: Line 373:
 
|cfu=5-20
 
|cfu=5-20
 
|image=KC_jc_third.jpg}}
 
|image=KC_jc_third.jpg}}
 +
 +
 +
{{Project template
 +
|title=Humanoid robotics
 +
|tutor=Giuseppina Gini(gini-AT-elet-DOT-polimi-DOT-it)
 +
|description=this project is about developing various functions of humanoids, in particular related to sensing and cognition for manipulation. Possible specific projects are:
 +
* BIOINSPIRED ROBOT HEAD FOR VISION - design and build a robot head able to host 2 cameras with 2dof of freedom each to create a human-like vision system. The movements can be obtained using 4 McKibben actuators for each camera, or electric actuators.
 +
* NEW HARDWARE FOR MAXIMUMOne - the humanoid robot is moved by more than 20 actuators and needs input from all of them. The new architecture FPGA based will move the arm and the head.
 +
* SIMULATOR OF HUMANOID ROBOT - complete the simulator of MaximumOne with all the dof. The simulator will use the same Matlab algorithms of the controller.
 +
* INTEGRATING MANIPULATION AND VISION ON MAXIMUMOne - develop a natural vision system that uses the neck and the eyes movements to follow objects and to concentrate on grasping targets. The integration can be done in matlab/Simulink and integrated in the MaximumOne model.
 +
* MANIPULATION ONTOLOGIES - develop an ontology approach to find the right way to grasp an object , considering both the object and the hand characteristics.
 +
* PATH PLANNING AND COLLISION AVOIDANCE IN OOPS - Randomized path planning is a strategy to produce paths for complex devices. An open source project (OOPS)  is available; the project is about integrating path planning with a robot simulator.
 +
 +
All the projects can be turned into a thesis.
 +
|start=Anytime
 +
|number=4-6
 +
|cfu=5-20
 +
|image=maximum.jpg}}
 +
 +
 +
{{Project template
 +
|title=Legged locomotion
 +
|tutor=[[User:Giuseppina Gini|Giuseppina Gini]] ([mailto:gini%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email])
 +
|description= The proposed projects in the area of walking robots will improve the performances of on-going systems.
 +
* KINEMATIC/DYNAMIC  MODEL OF WARUGADAR - develop a complete kinematic analysis of a quadruped robot, useful for planning the foot position on uneven terrains. The dynamic model will be useful for learning different gaits.
 +
* GAIT GENERATION AND CONTROL FOR WARUGADAR  - Study Central Pattern Generation, develop a CPG implementation in Matlab or Python. Adapt the method to a quadruped robot (Warugadar).
 +
* ROBO FISH - Continue the development of hardware and software for the robotic fish Zoidberg2, and study a fish colony.
 +
* EMBOT WALKING - complete the robot with 4 wheels used as feet. Control it and experiment.
 +
* ROBOTIC EXPERIMENTS WITH BIOLOID -  using Bioloid experiments hw and gaits, develop software for the humanoid challenges at ICRA2010.
 +
 +
All the projects can be turned into a thesis.
 +
|start=Anytime
 +
|number=2-5
 +
|cfu=5-20
 +
|image=leg.jpg}}
 +
 +
{{Project template
 +
|title=Robotic prosthesis
 +
|tutor=[[User:Giuseppina Gini|Giuseppina Gini]] ([mailto:gini%40%65%6c%65%74%2e%70%6f%6c%69%6d%69%2e%69%74 email])
 +
|description= The proposed projects in the development of an active hand prosthesis, novel in architecture since it considers anso the wrist. THe user interface is based on EMG signals.
 +
* ADVANCED EMG ANALYSIS - To develop prosthesis and therapeutic tools we need to analyze EMG signals according to position, velocity, force. Starting from signal acquisition develop in Matlab a model for force and velocity control.
 +
* HAND PROSTHESIS DESIGN - Define a virtual model of the hand prosthesis (actuation and sensors) and develop a controller based on multi-class classification of electro-myographic signals.
 +
 +
All the projects can be turned into a thesis.
 +
|start=Anytime
 +
|number=2-3
 +
|cfu=5-20
 +
|image=hand.jpg}}
  
 
<!--==== Soft Computing ====-->
 
<!--==== Soft Computing ====-->

Latest revision as of 19:53, 29 October 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.



BioSignal Analysis


Title: Human-computer interaction via voice recognition system
LURCH wheelchair.jpg
Description: We want develop a system to allow a voice interaction between the user and the wheelchair.

This project consists in develop one of the solutions proposed in literature and extended the LURCH software to include this kind of interface.

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux

References:

  • Phinx project [1]
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 1-2
CFU: 2.5-10


Brain-Computer Interface


Title: Driving an autonomous wheelchair with a P300-based BCI
LURCH wheelchair.jpg
Description: This project pulls together different Airlab projects with the aim to drive an autonomous wheelchair (LURCH) with a BCI, through the development of key software modules. Depending on the effort the student is willing to put into it, the project can grow to a full experimental thesis.
Tools and instruments
C++, C, BCI2000
Linux
Bibliography
R. Blatt et al. Brain Control of a Smart Wheelchair [2]
Tutor: Matteo Matteucci (email), Bernardo Dal Seno (email)
Start: November 2008
Number of students: 1
CFU: 5-20



Title: Reproduction of an algorithm for the recognition of error potentials
Bci arch.png
Description: Error potentials (ErrPs) are event-related potentials present in the EEG (electroencephalogram) when a subject makes a mistake or when the machine a subject is interacting with works in an expected way. They could be used in the BCI field to improve the performance of a BCI by automatically detecting classification errors.

The project aims at reproducing algorithms for ErrP detection from the literature.

Tools and instruments
Matlab
Bibliography
P.W. Ferrez, J. Millán. You Are Wrong! Automatic Detection of Interaction Errors from Brain Waves [3]
G. Schalk et al. EEG-based communication: presence of an error potential [4]
Tutor: Matteo Matteucci (email), Bernardo Dal Seno (email)
Start: This project has already been assigned
Number of students: 1
CFU: 5-15


Computer Vision and Image Analysis


Title: Environment Monitoring
Danch4.png
Description: The goal of this project is to develop a video surveillance system to track in 3D vehicles or people.

The idea is to use one or more calibrated camera to estimate the position and the trajectories of the moving objects in the scene. The skills required for this project are:

  • C/C++ and OpenCV library
  • Linux o.s.
  • Geometry/Image processing
  • Probabilistic robotics/IMAD

The project can be turned into a thesis extending the algorithm for a generic outdoor environment.

Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 2-3
CFU: 10-15



Title: Visual Merchandising
VisualM.jpg
Description: The goal of this project is to develop algorithms to count the number of products on the shelves of a market.

The idea is to use a calibrated camera to recognize the shelves, estimate the scale and improve the image quality. The skills required for this project are:

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux
  • Geometry/Image processing
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: As soon as possible
Number of students: 2-3
CFU: 2.5-15



Title: Analysis of patch recognition algorithms
Object.jpg
Description: Extract distinctive features from images is very important in computer vision application.

It can be used in algorithms for tasks like matching different views of an object or scene (e.g. for stereo vision) and object recognition. The aim of this work is to integrate in an existent framework the existing solution proposed in literature.

Skills

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux
  • Geometry/Image processing

References:

  • Oxford website [5]
  • Hess website [6]
  • Feature FAST [7]
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 2-3
CFU: 2.5-15



Title: Catadioptric MonoSLAM
Photo.jpg
Description: The goal of this work is to investigate a SLAM solutions based on catadioptric camera, integrating the solution presented in literature into an existing frameword.

Improvements could be the basis for a tesi.

Skills

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux
  • Geometry/Image processing

References:

  • Visual SLAM by Single Catadioptric Stereo [8]
  • Catadioptric reconstruction [9]
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 2-3
CFU: 2.5-15



Title: Trinocular Vision System (SUGR)
Trinoex.jpg
Description: A Trinocular Vision System is a device composed by three cameras that allows to measure 3D data (in this case segments) directly from images.

The aim of this tesina/project is to implement a trinocular algorithm based on SUGR, a library for Uncertain Projective Geometry.

Skills

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux
  • Geometry/Image processing
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: As soon as possible
Number of students: 2-3
CFU: 2.5-15



Title: GIFT and features extraction and description
Palla GIFT.jpg
Description: The idea is to improve and optimize the solution proposed by Campari et al. in their paper, who propose to estimate invariant descriptor using geodesic features descriptor based on color information.

Skills

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux
  • Geometry/Image processing
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 1-3
CFU: 10-20



Title: Multimedia Indexing Framework
CIR.gif
Description: The goal of this project is to develop a framework for multimedia indexing.

The idea is create an images database indexer that allows to make query using images or strings.

Skills

  • C/C++ and OpenCV library
  • Matlab (optionally)
  • Linux

References:

  • CBIR system definition [10]
  • Image database [11]
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 1-3
CFU: 2.5-15




Title: humanoid vision
Vision.jpg
Description: Our goal is to develop vision capabilities for a humanoiud robot. In particular:
  • NEURAL-BASED VISION SYSTEM - In this project we experiment different models of the neural structure of the visual cortex. In particular we collect couples of images with different fixation point and we reconstruct disparity, depth, shape recognition. A stereo disparity map is already available.
  • RECOGNITION OF HAND MOTIONS - Develop a system able to recognize the hand gestures from images of people. Use this for robot interfacing.
  • SEMANTIC MODELLING OF ACTIONS - Construct a semantic representation of actions to be matched against the data obtained from video/movements analysis.
Tutor: Giuseppina Gini (email)
Start: Anytime
Number of students: 1-3
CFU: 2.5-15


E-Science


Title: Knowledge discovery in life sciences
Life.jpg
Description: The goal of those projects is to develop methods and applications in the broad area of life sciences applications. Basic knowledge of chemistry and biology is useful.
  • DATA MINING FOR RULE INDUCTION - The project is about analysing large data sets to discover correlations between substructures and properties. CDK and WEKA are possible software to use.
  • IReNNS: LEARNING FROM STRUCTURES - This project will develop IReNNS, a recurrent neural net package, and develop new applications.
  • REC analysis in WEKA - The project is about theory and the implementation in Java of REC diagrams. A Matlab tool is available at http://www.cs.rpi.edu/~bij2/rec.html.
  • HOW TO TEACH SCIENCE - Propose a web site to teach University students a scientific topic using active participation and virtual experimentation.
  • CAUSAL REASONING - In this project we will develop the theory of causality proposed by Pearl and apply it to examples in biological sciences.

Other topics coming soon.

Tutor: Gini Giuseppina (email)
Start: Anytime
Number of students: 2-3
CFU: 5-20



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
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
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: 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.
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
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
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: 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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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 Competition
Keepaway.gif
Description: This project has the goal of participating to (and possibly winning ;)) the 2009 Reinforcement Learning competition. To have an idea of what participate to such a competition means you can have a look at the website of the 2008 RL competition.

The problems that will be proposed are still unknown. As soon as the domains will be published, the work will start by analyzing their main characteristics and, then we will identify which RL algorithms are most suited for solving such problems. After an implementation phase, the project will required a long experimental period to tune the parameters of the learning algorithms in order to improve the performance as much as possible.

Tutor: Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it)
Start: January, 2009
Number of students: 2-4
CFU: 10-20


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
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
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: 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: 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.

Tutor: [[DavidLaniado | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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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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), [[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


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



Title: Calibration of IMU-camera system
Imu cam big sphere.gif
Description: This work is about the problem to calibrate a system composed by an XSense

Inertial Measurement Unit and a Fire-i Camera. The pro ject will be focus on the problem to estimate both unknown rotation between the two devices and the extrinsic/intrinsic parameters of the camera. This algorithm allows to use the system for SLAM or robotics applications, like a wereable device for autonomous navigation or augmented reality.

Tools and instruments
Matlab/C++
Links
Matlab Toolbox for mutual calibration [12]
List of pubblications[13]
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 1
CFU: 5-20



Title: MonoSLAM system implementation
KC jc third.jpg
Description: The aim of this proposal is to investigate the different monocamera SLAM solution proposed in literature.

After a deepen bibliography research, the work will be focused on developing one of these algorithms into an existing framework and, only for tesi option, investigate possible improvements.

The algorithms interested are based on [14]:

  • Extended Kalman Filter [15]
  • Unscented Kalman Filter [16]
  • FastSLAM [17]
  • GraphSLAM [18]
Tools and instruments
Matlab/C++
Tutor: Matteo Matteucci (email), Davide Migliore (email)
Start: Anytime
Number of students: 1-2
CFU: 5-20




Title: Humanoid robotics
Maximum.jpg
Description: this project is about developing various functions of humanoids, in particular related to sensing and cognition for manipulation. Possible specific projects are:
  • BIOINSPIRED ROBOT HEAD FOR VISION - design and build a robot head able to host 2 cameras with 2dof of freedom each to create a human-like vision system. The movements can be obtained using 4 McKibben actuators for each camera, or electric actuators.
  • NEW HARDWARE FOR MAXIMUMOne - the humanoid robot is moved by more than 20 actuators and needs input from all of them. The new architecture FPGA based will move the arm and the head.
  • SIMULATOR OF HUMANOID ROBOT - complete the simulator of MaximumOne with all the dof. The simulator will use the same Matlab algorithms of the controller.
  • INTEGRATING MANIPULATION AND VISION ON MAXIMUMOne - develop a natural vision system that uses the neck and the eyes movements to follow objects and to concentrate on grasping targets. The integration can be done in matlab/Simulink and integrated in the MaximumOne model.
  • MANIPULATION ONTOLOGIES - develop an ontology approach to find the right way to grasp an object , considering both the object and the hand characteristics.
  • PATH PLANNING AND COLLISION AVOIDANCE IN OOPS - Randomized path planning is a strategy to produce paths for complex devices. An open source project (OOPS) is available; the project is about integrating path planning with a robot simulator.

All the projects can be turned into a thesis.

Tutor: Giuseppina Gini(gini-AT-elet-DOT-polimi-DOT-it)
Start: Anytime
Number of students: 4-6
CFU: 5-20




Title: Legged locomotion
Leg.jpg
Description: The proposed projects in the area of walking robots will improve the performances of on-going systems.
  • KINEMATIC/DYNAMIC MODEL OF WARUGADAR - develop a complete kinematic analysis of a quadruped robot, useful for planning the foot position on uneven terrains. The dynamic model will be useful for learning different gaits.
  • GAIT GENERATION AND CONTROL FOR WARUGADAR - Study Central Pattern Generation, develop a CPG implementation in Matlab or Python. Adapt the method to a quadruped robot (Warugadar).
  • ROBO FISH - Continue the development of hardware and software for the robotic fish Zoidberg2, and study a fish colony.
  • EMBOT WALKING - complete the robot with 4 wheels used as feet. Control it and experiment.
  • ROBOTIC EXPERIMENTS WITH BIOLOID - using Bioloid experiments hw and gaits, develop software for the humanoid challenges at ICRA2010.

All the projects can be turned into a thesis.

Tutor: Giuseppina Gini (email)
Start: Anytime
Number of students: 2-5
CFU: 5-20



Title: Robotic prosthesis
Hand.jpg
Description: The proposed projects in the development of an active hand prosthesis, novel in architecture since it considers anso the wrist. THe user interface is based on EMG signals.
  • ADVANCED EMG ANALYSIS - To develop prosthesis and therapeutic tools we need to analyze EMG signals according to position, velocity, force. Starting from signal acquisition develop in Matlab a model for force and velocity control.
  • HAND PROSTHESIS DESIGN - Define a virtual model of the hand prosthesis (actuation and sensors) and develop a controller based on multi-class classification of electro-myographic signals.

All the projects can be turned into a thesis.

Tutor: Giuseppina Gini (email)
Start: Anytime
Number of students: 2-3
CFU: 5-20