Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid

被引:175
作者
Herzog, Alexander [1 ]
Rotella, Nicholas [2 ]
Mason, Sean [2 ]
Grimminger, Felix [1 ]
Schaal, Stefan [1 ,2 ]
Righetti, Ludovic [1 ,2 ]
机构
[1] Max Planck Inst Intelligent Syst, Autonomous Mot Dept, D-72076 Tubingen, Germany
[2] Univ So Calif, Computat Learning & Motor Control Lab, Los Angeles, CA 90089 USA
基金
美国国家科学基金会;
关键词
Whole-body control; Multi-contact interaction; Hierarchical control; Inverse dynamics; Force control; Humanoid; LOCOMOTION;
D O I
10.1007/s10514-015-9476-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.
引用
收藏
页码:473 / 491
页数:19
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