Multi-objective robot motion planning using a particle swarm optimization model

作     者：Ellips MASEHIAN Davoud SEDIGHIZADEH 

作者机构：Faculty of EngineeringTarbiat Modares University 

出 版 物：《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑（计算机与电子（英文版）)

年 卷 期：2010年第11卷第8期

页      面：607-619页

核心收录：

学科分类：0810[工学-信息与通信工程] 080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Robot motion planning Particle swarm optimization Probabilistic roadmap Genetic algorithm 

摘      要：Two new heuristic models are developed for motion planning of point robots in known *** first model is a combination of an improved particle swarm optimization (PSO) algorithm used as a global planner and the probabilistic roadmap (PRM) method acting as a local obstacle avoidance *** the PSO component,new improvements are proposed in initial particle generation,the weighting mechanism,and position-and velocity-updating ***,two objective functions which aim to minimize the path length and oscillations,govern the robot’s movements towards its *** PSO and PRM components are further intertwined by incorporating the best PSO particles into the randomly generated *** second model combines a genetic algorithm component with the PRM *** this model,new specific selection,mutation,and crossover operators are designed to evolve the population of discrete particles located in continuous *** comparisons of the developed models with each other,and against the standard PRM method,show the advantages of the PSO method.