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

查看全文 作　　者：Ellips [1]MASEHIAN;Davoud [1]SEDIGHIZADEH

机构地区：[1]Faculty of Engineering,Tarbiat Modares University

出　　处：《Journal of Zhejiang University-Science C(Computers and Electronics)》索引2010年第11卷第8期,共13页

摘　　要：Two new heuristic models are developed for motion planning of point robots in known environments.The 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 planner.For the PSO component,new improvements are proposed in initial particle generation,the weighting mechanism,and position-and velocity-updating processes.Moreover,two objective functions which aim to minimize the path length and oscillations,govern the robot’s movements towards its goal.The PSO and PRM components are further intertwined by incorporating the best PSO particles into the randomly generated PRM.The second model combines a genetic algorithm component with the PRM method.In this model,new specific selection,mutation,and crossover operators are designed to evolve the population of discrete particles located in continuous space.Thorough comparisons of the developed models with each other,and against the standard PRM method,show the advantages of the PSO method. 关键词：Robot motion planning Particle swarm optimization Probabilistic roadmap Genetic algorithm

相关文献

参考文献（45）
引证文献（12）
耦合文献（0）

参考文献(45)

引证文献(12)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

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

参考文献(45)

引证文献(12)

用户提示