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Methods for indoor layout reconstruction must be significantly more tolerant to missing data than their outdoor counterparts, since environments such as offices and apartments exhibit extremely high levels of clutter, which typically results in heavy occlusions of walls and other structures of interest, large-scale artifacts, noise and missing data. The proposed work will be developed in collaboration with IRALAB, the Robotics Lab of University of Milano Bicocca.

The work will be based on an existing project, Free Your Camera (http://www.ira.disco.unimib.it/research/robotic-perception-research/free-your-camera-3d-indoor-scene-understanding-from-arbitrary-camera-motion/) and will be part of a robotic framework based on with ROS and in development at IRALAB.

The thesis will explore some of the aspects of the problem, eventually participating to the production of prototypes to be tested with real users. The thesis gives the possibility to develop a robot with special requirements, and to work with gesture interpretation by using devices such as Kinect or the WII Mote. The work is done in an interdisciplinary group including care givers and designers.

Material

• C++ modules for Extended Kalman Filtering
• libraries for automatic differentiation (http://www.autodiff.org/)

Expected outcome: New modules implementations based on automatic differentiation A comparison between the old stuff and new approach

Required skills or skills to be acquired:

• C++ programming under Linux

The robot first exhibition has been at Robotica 2009, within HI-Tech Expo at Fiera di Milano, on November 23-25, 2009. Here, the robot had to go around in an area delimited by a white stripe and contact verbally and with gestures people entering the area, in order to attract them to the booth.

Behaviors and gestures have still to be developed to come to an interesting and robust demo at next Robotica, or at other ehibits (e.g. at the Museo della Scienza of Milan).

No special skills are required, except basic c and object oriented programming.

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

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.

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

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.

• 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

Material

• A framework for multisensor SLAM using the world centric approach
• Papers and report about robocentric slam

Expected outcome:

• a fully functional robocentric version of the MoonSLAM framework

Required skills or skills to be acquired:

• Basic background in computer vision
• Background in Kalman filtering
• C++ programming under Linux

Material:

• a MS thesis which describes the scan matching algorithms
• a BS thesis which implements a prototype of the system

Expected outcome:

• a complete system that build maps integrating laser scan and visual informtion

Required skills or skills to be acquired:

• Background on Kalman filtering
• C++ programming under Linux

Material:

• datasets with real data
• a few odometric system implementations
• C++ libraries for non linear optimization

Expected outcome:

• software for the self calibration of a set of odometry systems mounted on the same robot

Required skills or skills to be acquired:

• C++ programming under Linux

The proposed project is aimed at extending USARSim along two directions:

• Development of a tool for automatically generating realistic 3D worlds for robot testing. This task involves work on 3D game modelling and development using the UDK engine.
• Create test arenas and perform experiment in USARSim. Simulation tools as USARSim are powerful tools for robotics, but in order to consider the results obtained in a virtual environment also valid in the real case, simulated environments must be validated through experiments performed both in virtually and with real robots.

Results will be included in the USARSim project and used by the RoboCup community.

• 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.

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.