Multi-robot GSA- and PSO-based optimal path planning in static environments

Abstract

This paper discusses new optimal path planning algorithms based on a Gravitational Search Algorithm (GSA) and on a Particle Swarm Optimization (PSO) algorithm applied to multiple mobile robots on holonomic wheeled platforms. Four path planning objectives are aggregated in the definition of a set of separate optimization problems for each robot. Each optimization problem involves a single scalar objective function (o.f.) expressed as the weighted sum of four o.f.s. The GSA and the PSO algorithm solve the optimization problems aiming the minimization of the o.f.s, and the path planning algorithms transform the solutions to the optimization problems into optimal solutions as optimal paths. The GSA-and PSO-based path planning algorithms are validated by several experiments with multiple robots that participate in missions.