Genetic Algorithm Based Solution to Dead-End Problems in Robot Navigation

摘要：

In robot navigation,mobile robots can suffer from dead-end problems,that is,they can be struck in areas which are surrounded by obstacles.Attempts have been reported to avoid a robot entering into such a dead-end area.However,in some applications,for example,rescue work,the dead-end areas must be explored.Therefore,it is vital for the robot to come out from the dead-end areas after exploration.This paper presents an approach which enables a robot to come out from dead-end areas.There are two main parts: a dead-end detection mechanism and a genetic algorithm (GA) based online training mechanism.When the robot realises that it is struck in a dead-end area,it will operate the online training to produce a new best chromosome that will enable the robot to escape from the area.

关键词： dead-end genetic algorithm path planning robot navigation.

作者: Xiaoming Kang Yong Yue Dayou Li Carsten Maple

作者单位: Department of Computing and Information SystemsUniversity of Bedfordshire,Park Square,Luton LU1 3JU Department of Computing and Information Systems University of Bedfordshire,Park Square,Luton LU1 3JU

会议类型: 国际会议

会议名称: International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)

会议地点: 上海

会议语种:英文

在线出版日期: 2008-06-29（万方平台首次上网日期，不代表论文的发表时间）