论文标题
使用粒子群优化在静态环境中的移动机器人路径计划
Mobile Robot Path Planning in Static Environments using Particle Swarm Optimization
论文作者
论文摘要
运动计划是机器人技术的关键要素，因为它使机器人能够自动导航。粒子群优化是一种简单而强大的优化技术，已在许多复杂的多维优化问题中有效地使用。本文提出了一种基于粒子群优化的路径规划算法，用于计算带有静态凸障碍的环境中的移动机器人最短路径。提出的算法通过对机器人起始和目标位置之间生成的网格线进行随机采样来找到最佳路径。通过模拟结果，针对不同方案的仿真结果说明了所提出的算法的功能。
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.
