Abstract

Swarm robotics is a decentralized approach to robotic systems. This paper investigates the problem of search and rescue using swarm robots. A multi-robot search algorithm using probabilistic finite state machine and interaction inspired by Lennard-Jones potential function has been proposed. Probabilistic finite state machine has been used to separate the tasks performed and to change coordination rules according to the circumstances and social probabilities. The approach is tested in various scenarios to test flexibility, scalability and robustness. The performance result is promising. Algorithmic complexity comparison with Robotic Darwinian Particle Swarm Optimization and Glowworm Swam Optimization appear favourable.

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