制御バリア関数とサンプリングを用いた人混み環境での安全なナビゲーション
Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions
時間ベースRRTに制御バリア関数を組み合わせ、歩行者予測モデルを用いて狭い屋内環境で動く障害物を避ける安全な経路計画を実現した。
著者: Keyvan Majd, Shakiba Yaghoubi, Tomoya Yamaguchi, Bardh Hoxha, Danil Prokhorov, Georgios Fainekos
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-based RRTs with Control Barrier Functions (CBFs) to generate, safe motion plans in dynamic environments with many pedestrians. Our framework is based upon a human motion prediction model which is well suited for indoor narrow environments. We demonstrate our approach on a high-fidelity model of the Toyota Human Support Robot navigating in narrow corridors. We show in three scenarios that our proposed online method can navigate safely in the presence of moving agents with unknown dynamics.
