信号時相論理を用いた安全性を考慮したモデル予測経路積分制御
Safety-aware Model Predictive Path Integral Control with Signal Temporal Logic
信号時相論理（STL）で表される制約を制御バリア関数に変換し、MPPIコントローラに組み込むことで、安全性と効率性を両立するサンプリングベースの計画手法を提案した。火星探査車とクアッドコプターの実験で有効性を示した。
著者: Yiqi Zhao, Taekyung Kim, Hideki Okamoto, Bardh Hoxha, Jyotirmoy V. Deshmukh, Lars Lindemann, Georgios Fainekos
分類: cs.RO, eess.SY
原文アブストラクト
Safety-aware motion planning remains a challenge in robotics, especially when missions are time-critical and are under complex specifications. In this paper, we propose safety-aware-stl-mppi, a computationally efficient sampling-based receding-horizon planning framework designed to promote satisfaction of constraints expressed in Signal Temporal Logic (STL). Our approach encodes discrete-time STL formulas into candidate time-varying control barrier functions (CBF), which are integrated into a model predictive path integral (MPPI) controller. Our method inherits the benefits of low computational cost from an efficiently parallelizable sampling based planner and utilizes CBF for constraints expressed in STL. We compare against several MPPI baselines using four artificial Mars Rover planning case studies with a diverse environment and cost setups, where we show our method consistently achieving high safety and efficiency. We show a quadcopter planning experiment with NVIDIA Isaac Lab.