Title :
Mobile Robot Path Planning Using an Improved Ant Colony Algorithm in Uncertain Environments
Author :
Shigang Cui ; Hui Wang ; Jigong Li
Author_Institution :
Tianjin Key Lab. of Inf. Sensing & Intell. Control, Tianjin Univ. of Technol. & Educ., Tianjin, China
Abstract :
As a swarm intelligence, ant colony algorithm (ACA) is widely used to solve the path planning problem. But ACA applied to the path planning has some disadvantages such as fall into local optimization easily and low convergence. In order to overcome these defects, we improved the ant colony algorithm by changing heuristic factor. The experiment results indicate that the improved algorithm performs better original algorithm.
Keywords :
mobile robots; optimisation; path planning; swarm intelligence; ACA; heuristic factor; improved ant colony algorithm; local optimization; mobile robot path planning; path planning problem; swarm intelligence; uncertain environments; Classification algorithms; Convergence; Heuristic algorithms; Optimization; Path planning; Robots; Search problems; ant colony algorithm; heuristic factor; path planning;
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/IMCCC.2013.49
