Mechanical PSO Aided by Extremum Seeking for Swarm Robots Cooperative Search

摘要：

　　This paper addresses the issue of swarm robots cooperative search.A swarm intelligence based algorithm, mechanical Particle Swarm Optimization (PSO), is first conducted which takes into account the robot mechanical properties and guiding the robots searching for a target.In order to avoid the robot localiza tion and to avoid noise due to feedback and measurements, a new scheme which uses Extremum Seeking (ES) to aid mechanical PSO is designed.The ES based method is capable of driving robots to the purposed states generated by mechani cal PSO without the necessity of robot localization.By this way, the whole robot swarm approaches the searched target cooperatively.This pilot study is verified by numerical experiments in which different robot sensors are mimicked.

关键词： Swarm Robotics Mechanical Particle Swarm Optimization Extremum Seeking Perturbation Cooperative Search

作者: Qirong Tang Peter Eberhard

作者单位: Institute of Engineering and Computational Mechanics,University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 64-71

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）