Difference between revisions of "VVV15 projects"
(add the project on iCub)
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= The crawling iCub =
= The crawling iCub =
Revision as of 10:49, 25 July 2015
Add here an entry for each project, please nominate a responsible person for each project.
IOL with Android in the Loop
Responsible: Alessandro Roncone
Participants: Alessandro Roncone, Vadim Tikhanoff, others
Short description: we have recently interfaced Android with YARP. We would like to modify the interactive object learning scenario so that the robot can be controlled with your phone. IOL in the loop, details.
Object Affordances Exploration
Responsible: Francesca Stramandinoli
Participants: Francesca, Francesco N., Ugo, Vadim, Daniele D.
Short description: Build an application that allows the iCub to explore object affordances
Responsible: Nawid Jamali
Participants: Nawid Jamali, Massimo Regoli and Takato Horii
Short description: use iCub's tactile sensors to extract contact-location independent features, explore and grasp an object.
Event-driven iCub development
Responsible: Arren Glover
Participants: Arren, Chiara, Marko, Samantha, Valentina
Short description: use iCub's event driven sensors to perform ball tracking, integrating modules for ego-motion compensation, SpiNNaker attention and face detection.
Responsible: Tobias Fischer
Contributors: T. Fischer, M. Petit, A.-L. Mealier, U. Pattacini, C. Moulin-Frier, J. Puigbo, J. Copete, B. Higy
Short description: The aim is to learn language proactively. There will be different `drives` 1) exploring, 2) triggering questions for labeling unknown objects in the objects properties collector. Pro-active tagging will be triggered because of either an (at the moment) unachievable goal, or because of the drive to explore.
Analysis and Control of iCub joint elasticity
Responsible: Nuno Guedelha
Participants: Nuno Guedelha, Daniele Pucci
Short description: The goal is to identify the joint flexibility parameters and integrate them in the motion controller model, for improving stability and accuracy. For the analysis, validation and performance evaluation, we will focus on the use case of a simple trajectory tracking.
The crawling iCub
Responsible : Serena Ivaldi
Group members : Marie Charbonneau, Dorian Goepp
There has been code used to make iCub crawl using Central Pattern Generators. We would like to use this code, port it to the current YARP version and use a learning/optimisation loop to tune the CPG's parameters. We shall detail this more on the project's page.