Fault-tolerance assessment of a Darwinian swarm exploration algorithm under communication constraints

Abstract

Ensuring a mobile ad-hoc network (MANET) in real and complex environments is an arduous task since the strength of the connection between two robots can rapidly change over time or even disappear. An extension of the Particle Swarm Optimization to multi-robot applications was recently proposed and denoted as Robotic Darwinian PSO (RDPSO). This paper contributes with a further extension of the RDPSO, by integrating a fault-tolerant distributed search in order to prevent communication network splits. To that end, each robot performs packet forwarding according to a paradigm of multi-hop communication, thus maintaining a maximum range or minimum signal quality between its k “best” neighbors. This results in a sum of k virtual forces for each robot to ensure a multi-connected MANET over time. Experimental results with 15 physical robots show that a more fault-tolerant strategy clearly influences the time needed to converge to the final solution but is less susceptible to robot failures.