A PSO-based algorithm designed for a swarm of mobile robots |
| |
Authors: | Qirong Tang Peter Eberhard |
| |
Affiliation: | (1) Institute of Engineering and Computational Mechanics, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany |
| |
Abstract: | This paper presents an algorithm called augmented Lagrangian particle swarm optimization with velocity limits (VL-ALPSO).
It uses a particle swarm optimization (PSO) based algorithm to optimize the motion planning for swarm mobile robots. Considering
problems with engineering constraints and obstacles in the environment, the algorithm combines the method of augmented Lagrangian
multipliers and strategies of velocity limits and virtual detectors so as to ensure enforcement of constraints, obstacle avoidance
and mutual avoidance. All the strategies together with basic PSO are corresponding to real situations of swarm mobile robots
in coordinated movements. This work also builds a swarm motion model based on Euler forward time integration that involves
some mechanical properties such as masses, inertias or external forces to the swarm robotic system. Simulations show that
the robots moving in the environment display the desired behavior. Each robot has the ability to do target searching, obstacle
avoidance, random wonder, acceleration or deceleration and escape entrapment. So, in summary due to the characteristic features
of the VL-ALPSO algorithm, after some engineering adaptation, it can work well for the planning of coordinated movements of
swarm robotic systems. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|