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.
| Original language | English |
|---|---|
| Pages (from-to) | 177-184 |
| Number of pages | 8 |
| Journal | International Journal of Computer Applications in Technology |
| Volume | 41 |
| Issue number | 3-4 |
| DOIs | |
| Publication status | Published - Sept 2011 |
| Externally published | Yes |
Keywords
- Dead end
- Genetic algorithm
- Obstacle avoidance
- Robot navigation