粒子群最適化を用いた静的環境における移動ロボットの経路計画
Mobile Robot Path Planning in Static Environments using Particle Swarm Optimization
静的で凸形状の障害物がある環境で、粒子群最適化により移動ロボットの最短衝突回避経路を計算するアルゴリズムを提案し、シミュレーションで有効性を示した。
著者: M. Shahab Alam, M. Usman Rafique, M. Umer Khan
分類: cs.RO
原文アブストラクト
Motion planning is a key element of robotics since it empowers a robot to navigate autonomously. Particle Swarm Optimization is a simple, yet a very powerful optimization technique which has been effectively used in many complex multi-dimensional optimization problems. This paper proposes a path planning algorithm based on particle swarm optimization for computing a shortest collision-free path for a mobile robot in environments populated with static convex obstacles. The proposed algorithm finds the optimal path by performing random sampling on grid lines generated between the robot start and goal positions. Functionality of the proposed algorithm is illustrated via simulation results for different scenarios.