未知環境における安全なナビゲーションのための局所占有格子地図からの制御バリア関数のオンライン合成
Online Synthesis of Control Barrier Functions with Local Occupancy Grid Maps for Safe Navigation in Unknown Environments
未知環境で局所占有格子地図から制御バリア関数をオンラインで高速合成し、リアルタイムの安全フィルタを実現する手法を提案。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Yuepeng Zhang, Yu Chen, Yuda Li, Shaoyuan Li, Xiang Yin
分類: cs.RO
原文アブストラクト
Control Barrier Functions (CBFs) have emerged as an effective and non-invasive safety filter for ensuring the safety of autonomous systems in dynamic environments with formal guarantees. However, most existing works on CBF synthesis focus on fully known settings. Synthesizing CBFs online based on perception data in unknown environments poses particular challenges. Specifically, this requires the construction of CBFs from high-dimensional data efficiently in real time. This paper proposes a new approach for online synthesis of CBFs directly from local Occupancy Grid Maps (OGMs). Inspired by steady-state thermal fields, we show that the smoothness requirement of CBFs corresponds to the solution of the steady-state heat conduction equation with suitably chosen boundary conditions. By leveraging the sparsity of the coefficient matrix in Laplace's equation, our approach allows for efficient computation of safety values for each grid cell in the map. Simulation and real-world experiments demonstrate the effectiveness of our approach. Specifically, the results show that our CBFs can be synthesized in an average of milliseconds on a 200 * 200 grid map, highlighting its real-time applicability.
