Path Planning for Deep Sea Mining Robot Based on ACO-PSO Hybrid Algorithm

摘要：

A ACO-PSO hybrid algorithm is proposed in order to resolve the path planning problem for deep-sea mining robots. In this study, the environment model was established by Bitmap method, and robot movement was simplified into particle movement by using Framework Space method. Ant colony optimization (ACO) is used to establish the corresponding solution, and some material algorithm steps are set out. Particle swarm optimization (PSO) is applied to optimize the parameters in ACO, and parameters can be selected self-adaptively. Results of simulation experiment demonstrate that this method can satisfy the precision demand of robots mining work in deep sea.

作者: Chunxue Shi Yingyong Bu Ziguang Li

作者单位: Department of Mechanical and Electronical Engineering Center South University Changsha, Hunan Provin Department of Automotive and Mechanical Engineering Changsha Science and Technology University Chang

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 125-129

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）