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Jedi Training Robogame +	Robogame where a drone is trying to hit by a laser a Jedi trainee who has to avoid it
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KartBot +	The goal of the project is to develop an interactive game between an autonomous robot and a remotely-controlled one, based on the metaphor of the game Mario Kart Wii.
King of the Hill +	Robogame where a robot should conquer hills, and a human player should contrast it
Krog +	Robot for playful interaction with children
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LARS and LASSO in non Euclidean Spaces +	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 # Tibshirani, R. (1996), Regression shrinkage and selection via the lasso. J. Royal. Statist. Soc B., Vol. 58, No. 1, pages 267-288 # Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani, Least Angle Regression, 2003
LCM middleware on embedded platform +	We are developing a framework for rapid prototyping of low-cost robotic systems. To fasten robot design and building, and to make software and hardware reuse easier, a modular architecture is mandatory. In a context of smart modules that have to cooperate by exchanging data to reach their common goal, the communication protocol and middleware are core components. This project is about the middleware component, a publish/subscribe system that takes care of managing topics, publisher and subscribers, and of marshaling data before sending it. This project aims at porting the LCM marshaling and middleware library, developed at MIT and used in the Grand Challenge competition, to embedded systems, in order to exploit the existing LCM tools and to be compliant with an existing and efficient technology. The project consists in: * stripping non necessary features of LCM to match the constraints of an embedded system and of the communication protocol * adding necessary features, like the concept of deadline (and priority as a consequence), that are mandatory for a real time distributed system * building a gateway, on an embedded platform, that acts as gateway between the standard-LCM world and the embededd-LCM network The projects has to be developed in ANSI C, and experience with embedded platforms is a plus.
LURCH - The autonomous wheelchair +	Augmenting commercial electric wheelchairs with autonomous navigation, obstacle avoidance, and multi-modal interfaces
Laser Game Bot +	Laser game between an autonomous robot and a remote controlled robot.
Lastnews +	Distributed web-content reader supporting Semantic tagging & item ranking.
Localization of E-2? +	Localization and navigation development for E-2?
Low Cost Laser Range Finder +	Development of a low cost Laser Range Finder
Low-cost IMU +	Characterization of a low-cost IMU module developed by AIRLab; use of such module to extract high-level information about human behavior.
Low-cost Robotics +	The project is aimed at developing tools and methodologies to support the design and implementation of low-cost robots, aimed at the mass market.
Lupin +	Development of a Robogame
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Machine Learning for Crop Weed Classification +	Automatic detection of crops and weeds by using image data
Mesh Refinement with Deep Learning +	Mesh Refinement with Deep Learning
Mining the Network of Coordination Interactions in Wikipedia +	This project aims to analyze the interactions between wiki users through the study of discussion pages (Talk: and User talk: namespaces).
Mining wikipedia categories +	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.
MoonSLAM Reengineering +	In the last three years a general framework for the implementation of EKF-SLAM algorithm has been developed at the AIRLab. After several improvements it is now time to redesign it based on the experience cumulated. The goal is to have an international reference framework for the development of EKF based SLAM algorithms with multiple sensors (e.g., lasers, odometers, inertial measurement ) and different motion models (e.g., free 6DoF motion, planar motion, ackerman kinematic, and do on). The basic idea is to implement it by using C++ templates, numerically stable techniques for Kalman filtering and investigation the use of automatic differentiation. It should be possible to seamlessly exchange motion model and sensor model without having to write code beside the motion model and the measurement equation. '''Material''' *lots of theoretical background and material *an existing (and working) C++ implementation of the framework '''Expected outcome:''' *a C++ library for the implementation of generic EKF-SLAM algorithms '''Required skills:''' *Experienced C++ programming under Linux
Mr. Mike +	The goal of the project is to develop an interactive robot for children affected by autism or phisical impairments. The robot reacts to the kid's manipulation showing different emotions.
Multimodal GUI for driving an autonomous wheelchair +	This project pulls together different Airlab projects with the aim to drive an autonomous wheelchair (LURCH - The autonomous wheelchair) with a multi modal interface (Speech Recognition, Brain-Computer Interface, etc.), through the development of key software modules. The work will be validated with live experiments. *R. Blatt et al. ''Brain Control of a Smart Wheelchair'' (http://tinyurl.com/ygldwun)
Multiobjective Reinforcement Learning Algorithms Elevator Group Control +	The goal of the project is to study MO RL algorithms and to apply them on an intelligent system for elevator group control.
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NaughtyFan +	Development of a robotic basket
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OWLIE +	An user-friendly, web-based application that provides collaborative editing for OWL ontologies, using classic and graphical notations
Object Recognition with Deep Boltzmann Machines +	Deep Boltzmann machines for classification tasks

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