A novel artificial bee colony optimization algorithm for global path planning of multi-robot systems
Lianhang Dou, Min Li, Yang Li, Qingying Zhao, Jie Li, Zhongya Wang · 2014
This paper presents a path planning and collision avoidance method based on artificial bee colony (ABC) optimization algorithm for multi-robot systems. Standard ABC algorithm can find a proper way for the robots quickly, but it still has shortcomings. An improved artificial bee colony optimization algorithm (IABC) is proposed to plan a reasonable collision-free path for each robot of a multi-robot system in complicated environment. Based on standard ABC algorithm, a new objective function is derived for global planning of each robot's path. The initialization strategy and fitness function are also optimized to improve the performance of IABC algorithm. Compared with standard ABC algorithm, IABC algorithm simplifies the parameter setting and achieves better performance. The feasibility and availability of the proposed IABC algorithm have been verified by simulation results.