Difference between revisions of "First Level Course Projects"
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|image=TORCS.jpg}} | |image=TORCS.jpg}} | ||
+ | {{Project template | ||
+ | |title= EyeBot. | ||
+ | |tutor= Alessandro Giusti (giusti-AT-elet-DOT-polimi-DOT-it), Daniele Loiacono (loiacono-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. | ||
+ | |start=Anytime | ||
+ | |number=1 to 2 | ||
+ | |cfu=5 to 12.5 | ||
+ | |image=TORCS2.jpg}} | ||
Revision as of 15:27, 9 October 2008
Here you can find a list of project proposals for the courses of "Progetto di Ingegneria Informatica" and "Progetto di Robotica" (5 CFU for each student)
Affective Computing
Title: | Affective VideoGames | |
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Description: | The goal of this activity is to develop an interactive video game (Car game, Shoot them up, Strategic game ..) able to adapt its behaviour in order to maximize your enjoyment. The game will measure your excitement by analizing your biological signals, which mirror your emotional state. The system will be able to adjust some parameters (i.e difficulty of car game circuits, opponents strength ...) in order to keep you egnagemet constant: "In your flow zone!".
Project phases:
These projects allow to experiment with biological-data acquisition tools and videogame design. Each project consists in the realization of one or more phases depending on the difficulty/cfu to be achieved and on the competences of the candidate(s) | |
Tutor: | Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 3 | |
CFU: | 2.5 to 20 |
Title: | Affective recognition in multimedia contexts | |
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Description: | The goal of this activity is to develop an interactive multimedia application (advertisement, e-learning, reccomendation system) able to capture your emotional state (interests, excitement, anger, joy) while watching at images, earing sounds etc. The application will measure your excitement by analyzing your biological signals, which mirror your emotional state. The system could be used to give feedback on the quality of multimedia content (i.e goodness of the advertisement, enjoyment of the movie ...)
Project phases:
These projects allow to experiment with biological-data acquisition tools and multimedia application design. Each project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s) | |
Tutor: | Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 3 | |
CFU: | 2.5 to 20 |
Title: | Affective robotics | |
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Description: | The goal of this activity is to develop an rehabilitation robotic game able to capture your emotional state (interests, excitement, anger, joy, stress) while interacting with the robot. The application will measure your excitement by analyzing your biological signals, which mirror your emotional state. The system could be used to adapt the therapy (executed by the game) according to the patient's needs. We believe the quality of the therapy is related to the subject's emotional state. The long term goal is to keep the user into a specific emotional state in order to maximize the therapy efficacy.
Project phases:
These projects allow to experiment with biological-data acquisition tools, robots and videogame design. Each project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s) | |
Tutor: | Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 3 | |
CFU: | 2.5 to 20 |
Title: | Driving companions | |
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Description: | The goal of this activity is to develop an applicationable to capture your emotional state (stress, attention level .. ) while driving standard cars. The application will measure the driver's stress level by analyzing his biological signals, which mirror the physiological state, and could be used to give feedbacks to the driver in dangerous situations.
Project phases:
These projects allow to experiment with biological-data acquisition tools, robots and videogame design. Each project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s) | |
Tutor: | Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 3 | |
CFU: | 2.5 to 20 |
Title: | Emotion from interaction | |
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Description: | The goal of this activity is to detect emotional states, such as stress or boreness from the interaction with the computer via mouse and keyboard (Emotion from Interaction). A library getting data from these devices has been already developed. Data have to be acquired in different situations and analyzed by neural networks or other classification tools already implemented. | |
Tutor: | Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 2 | |
CFU: | 5 to 12.5 |
Computer Vision and Image Analysis
Title: | Video surveillance system for indoor Environment | |
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Description: | The goal of this project is to develop a video surveillance system based on background subtraction algorithm. The idea is to use a single static camera to track moving objects in a known environment.
The skills required for this project are:
The project can be turned into a thesis extending the algorithm for camera network. | |
Tutor: | Matteo Matteucci (matteucci-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 2-3 | |
CFU: | 2.5-15 |
Machine Learning
Title: | Learning API for TORCS. | |
---|---|---|
Description: | 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 here) to simplify the development of controller using a learning framework.
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. | |
Tutor: | Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 2 | |
CFU: | 5 to 12.5 |
Title: | EyeBot. | |
---|---|---|
Description: | 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 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. | |
Tutor: | Alessandro Giusti (giusti-AT-elet-DOT-polimi-DOT-it), Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it), and Pierluigi Taddei (taddei-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1 to 2 | |
CFU: | 5 to 12.5 |
Robotics
Title: | Simulation of 6-DOF Robot Manipulator | |
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Description: | The goal of this project is to develop a simulator for a 6-DOF robot manipulator, using the ode (open dynamics engine) library for simulating the rigid body dynamics. The project involves three different phases:
This project allows to put into practice what has been explained during the first part of the course of Robotics. The project can be turned into a thesis, by using the simulated manipulator to perform some learning experiments. | |
Tutor: | Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 2-3 | |
CFU: | 10-15 |
Title: | Robot games | |
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Description: | The goal of this activity is to develop an interactive game with robots using commercial devices such as the WII Mote (see the Robogames page)
Projects are available in different areas:
These projects allow to experiment with real mobile robots and real interaction devices. The project can be turned into a thesis by producing a new game and robot. | |
Tutor: | Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1-2 | |
CFU: | 5-12.5 |
Title: | Robocup: soccer robots | |
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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 Robocup page and the MRT Team page)
Projects are available in different areas:
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: | Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it), Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it) | |
Start: | Anytime | |
Number of students: | 1-2 | |
CFU: | 5-12.5 |