Add here an entry for each project, please nominate a responsible person for each project.
- 1 IOL with Android in the Loop
- 2 Object Affordances Exploration
- 3 Tactile perception
- 4 Event-driven iCub development
- 5 Proactive Tagging
- 6 Analysis and Control of iCub joint elasticity
- 7 The crawling iCub
- 8 Object tracking in 3D
- 9 Balancing on a seesaw with the Purpley
- 10 Bayesian whole-body dynamics estimation
- 11 Analyzing the motion of iCub
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.
Link of the video of the demo : Video of the demo
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.
Object tracking in 3D
Responsible : Vadim Tikhanoff
Group members : Lilita Kiforenko
Short description: Detect and track some objects in 3D using pcl particle filter.
Balancing on a seesaw with the Purpley
Responsible : Daniele Pucci
Group members : Francesco Romano, Silvio Traversaro, Nuno Guedelha
We would like to carry on the first experiments of balancing on a seesaw with iCubGenova02, also known as the "Purpley". For the expected results, see
Bayesian whole-body dynamics estimation
Responsible : Francesco Nori
Group members : Claudia Latella, Silvio Traversaro, Francesco Nori
Group slides : File:VVV15-berdy.pdf
We would like to replicate the wholeBodyDynamicsTree module (for internal and external torque estimation module) within BERDY, which performs the same estimation in presence of multiple redundant measurements. Estimation is performed as a maximum-a-posteriori (MAP) strategy and it is framed in a Bayesian framework.
Analyzing the motion of iCub
Responsible : Alessia Vignolo
Group members : Roberto Barone, Carlos Cardoso, Alessia Vignolo
We would like to design some robot movements (artificial and natural ones) and analyze them using the informations taken from the encoders and the cameras.