异构多目标差分-动态窗口算法 及其在移动机器人中的应用

为了实现在多移动机器人和多窄通道的复杂动态环境中机器人的节能运动规划,提出异构多目标差分-动态窗口法(heterogeneous multi-objective differential evolution-dynamic window algorithm,HMODE-DWA).首先,建立行驶时间、执行器作用力和平滑度的3目标优化模型,设计具有碰撞约束的异构多目标差分进化算法来获得3个目标函数的最优解,进而在已知的静态环境中获得帕累托前沿,利用平均隶属度函数获得起点与终点间最优的全局路径;其次,定义基于环境缓冲区域的模糊动态窗口法使机器人完成动态复杂环境中避障,利用所提出的HMODE-DWA算法动态避障的同时实现节能规划.仿真和实验结果表明,所提出的混合路径规划控制策略能够有效降低移动机器人动态避障过程中的能耗.

Heterogeneous multi-objective differential evolution-dynamic window algorithm and application for energy-saving motion planning of mobile robot

Aiming at the problem of energy-saving motion path planning of the mobile robot in a complex unknown environment with mobile robots and multiple narrow channels, a hybrid algorithm based on the heterogeneous multi-objective differential evolution-dynamic window algorithm (HMODE-DWA) is proposed. Firstly, a three-objective optimization model of travel time, actuator force and smoothness is established. Secondly, a heterogeneous multi-objective differential evolution algorithm with collision constraints is designed to optimize three objective functions to obtain the Pareto frontier in a known static envoronment, and then, the optimal global path can be obtained using the average membership function. Thirdly, the robot uses the fuzzy dynamic window algorithm based on the environment buffer area to avoid obstacles in the unknown dynamic and complex environment. The global path nodes have been planned and used as the target points of the local planning for the robots to dynamically avoid obstacles and obtain the global optimal path. Finally, simulation experiments are given to verify the effectiveness of the proposed algorithm. The simulation results show that the proposed hybrid path planning control strategy can obtain the optimal global path and reduce the energy consumption during the dynamic obstacle avoidance process of mobile robots.