動的環境における安全なロボットナビゲーションのためのセンサベース分布ロバスト制御
Sensor-Based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments
ノイズを含むオンボードセンサ情報を直接取り込む分布ロバスト制御バリア関数(DR-CBF)を提案し、経路追従のための制御リアプノフ関数と組み合わせることで、不確実な動的環境下でも安全かつ効率的な移動ロボットのナビゲーションを実現した。
著者: Kehan Long, Yinzhuang Yi, Zhirui Dai, Sylvia Herbert, Jorge Cortés, Nikolay Atanasov
分類: cs.RO, cs.SY, eess.SY, math.OC
原文アブストラクト
We introduce a novel method for mobile robot navigation in dynamic, unknown environments, leveraging onboard sensing and distributionally robust optimization to impose probabilistic safety constraints. Our method introduces a distributionally robust control barrier function (DR-CBF) that directly integrates noisy sensor measurements and state estimates to define safety constraints. This approach is applicable to a wide range of control-affine dynamics, generalizable to robots with complex geometries, and capable of operating at real-time control frequencies. Coupled with a control Lyapunov function (CLF) for path following, the proposed CLF-DR-CBF control synthesis method achieves safe, robust, and efficient navigation in challenging environments. We demonstrate the effectiveness and robustness of our approach for safe autonomous navigation under uncertainty in simulations and real-world experiments with differential-drive robots.
