AutoRVO: 動的制約を考慮した密集異種交通における局所ナビゲーション
AutoRVO: Local Navigation with Dynamic Constraints in Dense Heterogeneous Traffic
車・三輪車・自転車・歩行者が混在する密集交通で、各エージェントの運動学的・動的制約を考慮しつつ相互速度障害物に基づく最適化で衝突のない滑らかな軌道を計算する手法を提案した。
著者: Yuexin Ma, Dinesh Manocha, Wenping Wang
分類: cs.RO, cs.MA
原文アブストラクト
We present a novel algorithm for computing collision-free navigation for heterogeneous road-agents such as cars, tricycles, bicycles, and pedestrians in dense traffic. Our approach currently assumes the positions, shapes, and velocities of all vehicles and pedestrians are known and computes smooth trajectories for each agent by taking into account the dynamic constraints. We describe an efficient optimization-based algorithm for each road-agent based on reciprocal velocity obstacles that takes into account kinematic and dynamic constraints. Our algorithm uses tight fitting shape representations based on medial axis to compute collision-free trajectories in dense traffic situations. We evaluate the performance of our algorithm in real-world dense traffic scenarios and highlight the benefits over prior reciprocal collision avoidance schemes.
