Author(s)

Jin Zhou, Michael Biney, Xu E, Chunxiao Liu and Yanhong Li

Corresponding Author

Xu E

ABSTRACT

Deadlock in robotics can be a frustrating problem if ignored. It is described as a halt state where two threads wait on each other to release a resource. The recent rise in the use of ant colony algorithms in solving problems is what inspired this paper. Several heuristic methods for finding a solution to this problem have been designed hence the improvement of the ACO algorithm. This paper is devoted to solving deadlock problems in robotic mapping with the ant colony algorithm by improving on the traditional ACO to achieve efficient recovery techniques during robotic mapping. It also outlines the use of mathematical functions of the ACO to influence robots in their probabilistic decision making in a deadlock state. Results from this paper prove that the improved ACO with the retraction mechanism is more efficient and increases the differences of results and is useful to discover the ideal way.

KEYWORDS

Deadlock; mapping; ACO; stigmergy; retraction