微分可能最適化に基づく時変制御バリア関数による動的障害物回避
Differentiable Optimization Based Time-Varying Control Barrier Functions for Dynamic Obstacle Avoidance
微分可能最適化で構築した制御バリア関数を時変形に拡張し、動的な障害物を避ける安全制御を実現、7自由度マニピュレータで実証した。
著者: Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy, Farshad Khorrami
分類: cs.RO
原文アブストラクト
Control barrier functions (CBFs) provide a simple yet effective way for safe control synthesis. Recently, work has been done using differentiable optimization (diffOpt) based methods to systematically construct CBFs for static obstacle avoidance tasks between geometric shapes. In this work, we extend the application of diffOpt CBFs to perform dynamic obstacle avoidance tasks. We show that by using the time-varying CBF (TVCBF) formulation, we can perform obstacle avoidance for dynamic geometric obstacles. Additionally, we show how to extend the TVCBF constraint to consider measurement noise and actuation limits. To demonstrate the efficacy of our proposed approach, we first compare its performance with a model predictive control based method and a circular CBF based method on a simulated dynamic obstacle avoidance task. Then, we demonstrate the performance of our proposed approach in experimental studies using a 7-degree-of-freedom Franka Research 3 robotic manipulator.
