Title :
Swarm Intelligence: Ant-Based Robot Path Planning
Author :
Zhou, Jing ; Dai, Guan-Zhong ; He, De-Quan ; Ma, Jun ; Cai, Xiao-Yan
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
In this paper we proposed a novel algorithm ant-based robot path planning (ARPP) based on ant colony system (ACS) to mimic a swarm of ants to find the globally optimal path for autonomous mobile robots. Visibility graph was used as both the roadmap and construction graph in ARPP. Although the near-optimums were readily available by ARPP, it is hard to find the optimality; therefore we proposed the special ARPP (S-ARPP) algorithm as its supplement. Experimental results show S-ARPP outperforms ARPP for higher qualities of the global-best path it found, and a flexible trade-off between satisfactory solutions and the number of iterations was also easily available to meet the certain needs.
Keywords :
graph theory; mobile robots; particle swarm optimisation; path planning; ant colony system; autonomous mobile robots; construction graph; special ant-based robot path planning; swarm intelligence; visibility graph; Ant colony optimization; Distributed computing; Helium; Information security; Intelligent robots; Mobile robots; Particle swarm optimization; Path planning; Robot kinematics; Robotics and automation; S-ARPP; ant colony system; ant-based robot path planning; visibility graph;
Conference_Titel :
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location :
Xian
Print_ISBN :
978-0-7695-3744-3
DOI :
10.1109/IAS.2009.120