Title
Target Attraction-Based Ant Colony Algorithm For Mobile Robots In Rescue Missions
Keywords
ACO; Ant colony optimization; Dynamic path planning; Robot rescue; Target attraction
Abstract
After an earthquake, the road conditions are usually unknown and hazardous, which poses a great challenge for mobile robots to plan paths and reach the goal position safely for rescue operations. This paper presents a target attraction-based ant colony (TAAC) algorithm for the dynamic path planning of mobile robots operated in rescue missions. The global information of the road map is deployed to establish a target attraction function so that the probability of selecting an optimal path to the goal node is improved and the probability of converging to a local minimum path is reduced. Simulation results show that the proposed TAAC algorithm has a better dynamic performance and a faster convergence speed, compared with the existing max-min ant system algorithm. Copyright © 2012 Inderscience Enterprises Ltd.
Publication Date
1-1-2012
Publication Title
International Journal of Modelling, Identification and Control
Volume
17
Issue
2
Number of Pages
133-142
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1504/IJMIC.2012.048920
Copyright Status
Unknown
Socpus ID
84866041293 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84866041293
STARS Citation
Zhang, Xiaoyong; Peng, Jun; Hu, Huosheng; Lin, Kuo Chi; and Wang, Jing, "Target Attraction-Based Ant Colony Algorithm For Mobile Robots In Rescue Missions" (2012). Scopus Export 2010-2014. 5507.
https://stars.library.ucf.edu/scopus2010/5507