Distributed cohesive configuration control for swarm robots with boundary information and network sensing

Abstract

In this paper, we present flocking with cohesive configuration control - motion controllers that allow multiple robots to move through the environment as a coherent group while maintaining connectivity and density invariants. We start with a flocking controller from the literature. First, we produce a boundary force on robots that are on the internal and external boundaries of the configuration. This removes concave regions of the boundary, producing a convex configuration with uniform density. Second, we solve interstitial lattice errors caused by robots clumping too close together by moving them towards the boundary with a clump remover algorithm. Finally, we determine when a configuration is on the verge of disconnecting by identifying local articulation points; regions where the removal of a single robot will change the local topology. When one is detected, we switch modes to a clustering algorithm that draws robots to the vulnerable region. The combination of these algorithms produces a cohesive configuration controller. We verify our resulting controller with simulations from random initial conditions and selected extreme cases. Simulation results show the controller successfully forms a configuration with natural resting density in twelve of trials and maintains connectivity in twelve trials. We also provide real-world experiments to show that proposed algorithms work under low-resolution sensor platforms.