論理で歩く：信号時相論理ガイド型モデル予測制御による外乱に頑健な二足歩行
Walking-by-Logic: Signal Temporal Logic-Guided Model Predictive Control for Bipedal Locomotion Resilient to External Perturbations
信号時相論理（STL）をモデル予測制御に組み込み、外乱を受けた二足歩行ロボットがタスク仕様を満たしつつロバスト性を最大化する復帰軌道を生成する枠組みを提案した。
著者: Zhaoyuan Gu, Rongming Guo, William Yates, Yipu Chen, Ye Zhao
分類: cs.RO
原文アブストラクト
This study proposes a novel planning framework based on a model predictive control formulation that incorporates signal temporal logic (STL) specifications for task completion guarantees and robustness quantification. This marks the first-ever study to apply STL-guided trajectory optimization for bipedal locomotion push recovery, where the robot experiences unexpected disturbances. Existing recovery strategies often struggle with complex task logic reasoning and locomotion robustness evaluation, making them susceptible to failures caused by inappropriate recovery strategies or insufficient robustness. To address this issue, the STL-guided framework generates optimal and safe recovery trajectories that simultaneously satisfy the task specification and maximize the locomotion robustness. Our framework outperforms a state-of-the-art locomotion controller in a high-fidelity dynamic simulation, especially in scenarios involving crossed-leg maneuvers. Furthermore, it demonstrates versatility in tasks such as locomotion on stepping stones, where the robot must select from a set of disjointed footholds to maneuver successfully.
