Semantic search

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%7Ccenter%7C300px]]

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.|center|300px]]

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|center|300px]]

• B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf)
• B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)%7Ccenter%7C300px]]

Material:

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

Expected outcome:

• An extended Kalman filter which uses this new representation

Required skills or skills to be acquired:

• Good mathematical background
• C++ programming under Linux|center|300px]]

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".|center|300px]]

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.|center|300px]]

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

References

• Drivatar in Forza Motorsport (http://research.microsoft.com/en-us/projects/drivatar/default.aspx)
• TORCS (http://torcs.sourceforge.net/ TORCS)
• Botprize (http://botprize.org/)
• Daniele Loiacono's AI&R Lab Projects (http://home.dei.polimi.it/loiacono/uploads/Teaching/HomePage/AIRLab_AA20092010.pdf)%7Ccenter%7C300px]]

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.|center|300px]]

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|center|300px]]

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

The project consists in:

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

The projects has to be developed in ANSI C, and experience with embedded platforms is a plus.|center|300px]]

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.|center|300px]]

Material

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

Expected outcome:

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

Required skills:

• Experienced C++ programming under Linux|center|300px]]

• R. Blatt et al. Brain Control of a Smart Wheelchair (http://tinyurl.com/ygldwun)%7Ccenter%7C300px]]

Material:

• existing prototypical implementation of the system

Expected outcome:

• an odometric sensor for planar odometry with uncalibrated camera

Required skills or skills to be acquired:

• Good mathematical background
• Backgroundd in computer vision
• C++ programming under Linux|center|300px]]