Genetic algorithm based solution to dead-end problems in robot navigation. (27th September 2011)

• Record Type: Journal Article
• Authors: Kang, Xiaoming; Yue, Yong; Li, Dayou; Maple, Carsten
• Is Part Of: International journal of computer applications technology. Volume 41:Number 3/4(2011)
• Page Start: 177
• Page End: 184
• Publication Date: 2011-09-27
• Subjects: dead end areas -- genetic algorithms -- obstacle avoidance -- robot navigation -- mobile robots -- robotic exploration -- dead-end detection -- escape mechanisms -- dead ends; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

In robot navigation, mobile robots can suffer from dead-end problems, that is, they can be stuck 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 stuck 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.