TAILIEUCHUNG - Swarm Optimization Approach for Light Source Detection by Multi-robot System
In this paper, a modified Particle Swarm Optimization Algorithm (PSO) was presented for MRS on detecting light sources, namely APSO. In the proposed algorithm, an integration of conventional PSO and Artificial Potential Field (APF) is employed to use swarm intelligence for space exploration and light source detection. | VNU Journal of Science: Comp. Science & Com. Eng., Vol. 32, No. 3 (2016) 1-10 Swarm Optimization Approach for Light Source Detection by Multi-robot System1 Hoang Anh Quy, Pham Minh Trien VNU University of Engineering and Technology, 144 Xuan Thuy, Cau Giay, Hanoi, Vietnam Abstract Exploration and searching in unknown or hazardous environments using multi-robot systems (MRS) is among the principal topics in robotics. There have been numerous works on searching and detection of odor, fire or pollution sources. In this paper, a modified Particle Swarm Optimization Algorithm (PSO) was presented for MRS on detecting light sources, namely APSO. In the proposed algorithm, an integration of conventional PSO and Artificial Potential Field (APF) is employed to use swarm intelligence for space exploration and light source detection. The formulas for APSO velocities are based on those of PSO and APF. Furthermore, each particle is surrounded by an APF that forms repulsive force to prevent collision while the swarm is in operation. The simulation results of APSO in Matlab by various scenarios confirmed the reliability and efficiency of the proposed algorithm. Received 04 December 2015, Revised 09 January 2016, Accepted 26 September 2016 Keywords: PSO, MRS, APF, APSO, light source detection. 1. Introduction* because of its efficiency, intuitiveness and simplicity. Motivated by social searching behavior of natural swarm, PSO is especially effective in optimization problems and widely applied in various fields. Searching tasks of MRS are in fact optimization problems, in which the robots attempt to locate the regions or spots of extreme signal intensity. Although the idea of applying PSO to multi-robot search is not novel, many problems still need to be addressed adequately in order to put that idea into practice. Some of them are proneness to collision and premature convergence. Many of the related works are concerned with improving performance of the MRS. In [5], the authors .
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