Genetic algorithm based solution to dead-end problems in robot navigation
Issue Date
2011Subjects
dead end areasgenetic algorithms
obstacle avoidance
robot navigation
mobile robots
robotic exploration
dead-end detection
escape mechanisms
dead ends
Metadata
Show full item recordAbstract
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.Citation
Genetic algorithm based solution to dead-end problems in robot navigation 2011, 41 (3/4):177-184 International Journal of Computer Applications in TechnologyPublisher
InderscienceAdditional Links
http://www.inderscience.com/link.php?id=42693Type
ArticleLanguage
enISSN
0952-80911741-5047
ae974a485f413a2113503eed53cd6c53
10.1504/IJCAT.2011.042693