脚式ロボットの全身運動計画のためのハイブリッドシステムDDP
Hybrid Systems Differential Dynamic Programming for Whole-Body Motion Planning of Legged Robots
状態依存の切り替えを伴うハイブリッドシステム向けに、衝撃対応DDP・拡張ラグランジュ法・切り替え時間最適化を統合したHS-DDPを提案し、MIT Mini Cheetahのバウンディング歩容で有効性を示した。
著者: He Li, Patrick M. Wensing
分類: cs.RO
原文アブストラクト
This paper presents a Differential Dynamic Programming (DDP) framework for trajectory optimization (TO) of hybrid systems with state-based switching. The proposed Hybrid Systems DDP (HS-DDP) approach is considered for application to whole-body motion planning with legged robots. Specifically, HS-DDP incorporates three algorithmic advances: an impact-aware DDP step addressing the impact event in legged locomotion, an Augmented Lagrangian (AL) method dealing with the switching constraint, and a Switching Time Optimization (STO) algorithm that optimizes switching times by leveraging the structure of DDP. Further, a Relaxed Barrier (ReB) method is used to manage inequality constraints and is integrated into HS-DDP for locomotion planning. The performance of the developed algorithms is benchmarked on a simulation model of the MIT Mini Cheetah executing a bounding gait. We demonstrate the effectiveness of AL and ReB for handling switching constraints, friction constraints, and torque limits. By comparing to previous solutions, we show that the STO algorithm achieves 2.3 times more reduction of total switching times, demonstrating the efficiency of our method.
