A new multi-robot search algorithm using Probabilistic Finite State Machine and Lennard-Jones potential function

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.