Dynamic Seaching and Guidance of Swarm Robots with Particle Swarm Optimization

This is a two-year term project, where the particle swarm optimization (PSO) algorithm is utilized for swarm-robot systems. The goals of this project include target searching, formation control, obstacle avoidance, and cooperative movement. The topics of concern consist of the study of swarm theory, mobile robot design and implementation, static/dynamic target searching and guidance. In the swarm theory, a randomly searching mechanism will be introduced to avoid premature convergence in local optima in a dynamical varying environment. Stochastic adaptive PSO has the advantages that few parameters are required to be tuned and the re-searching ability is significantly improved. A self-design and -implement swarm robots system will be considered for the proposed algorithms. It is optimistic to see that that the research results will make progress for the intelligent evolutionary computation and the design of intelligent robots.

Project ID:PB9808-2393
External Project ID:NSC98-2221-E182-042-MY2