[PAST] Multi-Contact Motion Computations for Humanoid Robots
[PAST] Multi-Contact Motion Computations for Humanoid Robots 
2014 / 01 / 10 / AM 11:00
Location: 301 - 201
Speaker: Abderrahmane Kheddar
Abderrahmane KHEDDAR received the BS in Computer Science from the Institut National d'Informatique (INI), Algiers, and the MSc and Ph.D. degree in robotics, both from the University of Pierre et Marie Curie, Paris 6. He is presently Directeur de Recherche at CNRS and the Director of the CNRS-AIST Joint Robotic Laboratory (JRL), UMI3218/CRT, Tsukuba, Japan. He is also leading the Interactive Digital Humans (IDH) team at CNRS-UM2 LIRMM at Montpellier, France. His research interests include haptics, humanoids and more recently thought-based control using brain machine interfaces. He is a founding member of the IEEE/RAS chapter on haptics (acting also as a senior advisor), the co-chair and founding member of the IEEE/RAS Technical committee on model-based optimization, Editor of the IEEE Transactions on Robotics, and a member of the editorial board of the Journal of Intelligent and Robotic Systems, PRESENCE, and Frontiers of Bionics. He is a founding member of the IEEE Transactions on Haptics and served in its editorial board from 2007 to 2010.
This talk sums up the main achievements at the CNRS-AIST Joint Robotics Laboratory (JRL), with a focus on the limitations in using model-based optimization techniques to plan multi-contact dynamic motion for humanoid robots without model reduction; that is to say, considering all the degrees of freedom with limitations, constraints, together with multi-contact non-gaited transitions. We describe recent results in the way we handle constraints to enforce their fulfillment independently from the grid granularity, i.e., all along the time-trajectory. Using Taylor series expansions, the problem can be written as a semi-infinite programming problem, where constraints and the cost function are time-polynomials in which coefficients are functions of the optimization parameters. We also discuss the particular case of the distance function and its evaluation in this framework.