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Centroidal Trajectory Generation and Stabilization based on Preview Control for Humanoid Multi-contact Motion
Masaki Murooka, Mitsuharu Morisawa, Fumio Kanehiro
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Multi-contact motion is important for humanoid robots to work in various environments. We propose a centroidal online trajectory generation and stabilization control for humanoid dynamic multi-contact motion. The proposed method features the drastic reduction of the computational cost by using preview control instead of the conventional model predictive control that considers the constraints of all sample times. By combining preview control with centroidal state feedback for robustness to disturbances and wrench distribution for satisfying contact constraints, we show that the robot can stably perform a variety of multi-contact motions through simulation experiments.
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