混雑環境における車型ロボット群の分散計画
Decentralized Planning for Car-Like Robotic Swarm in Cluttered Environments
混雑環境でリアルタイムに経路計画を行う車型ロボット群の分散フレームワークを提案し、シミュレーションと実機実験で有効性を検証した。
著者: Changjia Ma, Zhichao Han, Tingrui Zhang, Jingping Wang, Long Xu, Chengyang Li, Chao Xu, Fei Gao
分類: cs.RO
原文アブストラクト
Robot swarm is a hot spot in robotic research community. In this paper, we propose a decentralized framework for car-like robotic swarm which is capable of real-time planning in cluttered environments. In this system, path finding is guided by environmental topology information to avoid frequent topological change, and search-based speed planning is leveraged to escape from infeasible initial value's local minima. Then spatial-temporal optimization is employed to generate a safe, smooth and dynamically feasible trajectory. During optimization, the trajectory is discretized by fixed time steps. Penalty is imposed on the signed distance between agents to realize collision avoidance, and differential flatness cooperated with limitation on front steer angle satisfies the non-holonomic constraints. With trajectories broadcast to the wireless network, agents are able to check and prevent potential collisions. We validate the robustness of our system in simulation and real-world experiments. Code will be released as open-source packages.
