Whole-body Model-Predictive Control applied to the HRP-2 Humanoid

  • Posted on: 9 September 2015
  • By: ostasse
TitleWhole-body Model-Predictive Control applied to the HRP-2 Humanoid
Publication TypeConference Paper
Year of Publication2015
AuthorsKoenemann, J, Del Prete, A, Tassa, Y, Todorov, E, Stasse, O, Bennewitz, M, Mansard, N
Conference NameIEEE International Conference on Intelligent Robots and Systems (IROS 2015)
KeywordsWhole body motion control
Abstract

Controlling the robot with a permanently-updated optimal trajectory, also known as model predictive control, is the Holy Grail of whole-body motion generation. Before obtaining it, several challenges should be faced: computation cost, non-linear local minima, algorithm stability, etc. In this paper, we address the problem of applying the updated optimal control in real-time on the physical robot. In particular, we focus on the problems raised by the delays due to computation and by the differences between the real robot and the simulated model. Based on the optimal-control solver MuJoCo, we implemented a complete model-predictive controller and we applied it in real-time on the physical HRP-2 robot. It is the first time that such a whole-body model predictive controller is applied in real-time on a complex dynamic robot. Aside from the technical contributions cited above, the main contribution of this paper is to report the experimental results of this premi` ere
 implementation.

 

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