摘要
服务机器人仿真主要研究基于真实场景中服务机器人在完成多个任务时的最优行动路径和行动序列规划。多种群遗传算法在标准遗传算法基础上将遗传算法拆分在多个子种群间并行进行,通过子种群之间的信息交换以增加种群中个体的多样性,从而避免传统遗传算法早熟收敛、局部搜索能力差等问题的发生。将多种群遗传算法与服务机器人仿真系统相结合研究家服务机器人的行动路径规划。
The simulation of service robots mainly studies the optimal path and sequence planning of service robots when they complete multiple tasks in real scenes.Multi-population genetic algorithm divides genetic algorithm into several sub-populations on the basis of standard genetic algorithm and carries out parallel operation.By exchanging information among sub-populations,it can increase the diversity of individuals in the population,thus avoiding premature convergence and poor local search ability of traditional genetic algorithm.This paper combines multi-population genetic algorithm with service robot simulation system to study the path planning of service robot.
出处
《工业控制计算机》
2019年第5期106-107,共2页
Industrial Control Computer
关键词
多种群遗传算法
服务机器人仿真
规划
multi-population genetic algorithm
service robot simulation
planning
