重心運動量モデルに基づく非周期的二足歩行のロバスト最適計画と制御
Robust Optimal Planning and Control of Non-Periodic Bipedal Locomotion with A Centroidal Momentum Model
重心運動量ダイナミクスに基づき、非周期的なキーフレーム状態をロバストに追従する二足歩行の計画・制御手法を提案し、様々な地形や外乱下での有効性をシミュレーションで示した。
著者: Ye Zhao, Benito R. Fernandez, Luis Sentis
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This study presents a theoretical method for planning and controlling agile bipedal locomotion based on robustly tracking a set of non-periodic keyframe states. Based on centroidal momentum dynamics, we formulate a hybrid phase-space planning and control method which includes the following key components: (i) a step transition solver that enables dynamically tracking non-periodic keyframe states over various types of terrains, (ii) a robust hybrid automaton to effectively formulate planning and control algorithms, (iii) a steering direction model to control the robot's heading, (iv) a phase-space metric to measure distance to the planned locomotion manifolds, and (v) a hybrid control method based on the previous distance metric to produce robust dynamic locomotion under external disturbances. Compared to other locomotion methodologies, we have a large focus on non-periodic gait generation and robustness metrics to deal with disturbances. Such focus enables the proposed control method to robustly track non-periodic keyframe states over various challenging terrains and under external disturbances as illustrated through several simulations.
