A Distributed Epigenetic Shape Formation and Regeneration Algorithm for a Swarm of Robots

TL;DR

This paper introduces a distributed algorithm inspired by epigenetic tracking that enables a swarm of robots to form arbitrary shapes and regenerate them after damage, using local interactions without central control.

Contribution

It presents a novel ET-based algorithm for shape formation and regeneration in robot swarms, emphasizing distributed control and local computation.

Findings

Robots successfully form complex shapes in simulation.

The algorithm enables shape regeneration after damage or splitting.

Shape scaling is achieved during regeneration.

Abstract

Living cells exhibit both growth and regeneration of body tissues. Epigenetic Tracking (ET), models this growth and regenerative qualities of living cells and has been used to generate complex 2D and 3D shapes. In this paper, we present an ET based algorithm that aids a swarm of identically-programmed robots to form arbitrary shapes and regenerate them when cut. The algorithm works in a distributed manner using only local interactions and computations without any central control and aids the robots to form the shape in a triangular lattice structure. In case of damage or splitting of the shape, it helps each set of the remaining robots to regenerate and position themselves to build scaled down versions of the original shape. The paper presents the shapes formed and regenerated by the algorithm using the Kilombo simulator.