A Parallel Distributed Strategy for Arraying a Scattered Robot Swarm

TL;DR

This paper presents a distributed algorithm for organizing a scattered robot swarm into an evenly spaced array, optimizing time, communication, and travel without central control.

Contribution

It introduces a novel multi-stage distributed method for arraying robots efficiently without central authority, achieving optimal parallelization.

Findings

Arraying completed in O(n) time

Uses O(n^2) messages for communication

Travel distance is O(nD)

Abstract

We consider the problem of organizing a scattered group of $n$ robots in two-dimensional space, with geometric maximum distance $D$ between robots. The communication graph of the swarm is connected, but there is no central authority for organizing it. We want to arrange them into a sorted and equally-spaced array between the robots with lowest and highest label, while maintaining a connected communication network. In this paper, we describe a distributed method to accomplish these goals, without using central control, while also keeping time, travel distance and communication cost at a minimum. We proceed in a number of stages (leader election, initial path construction, subtree contraction, geometric straightening, and distributed sorting), none of which requires a central authority, but still accomplishes best possible parallelization. The overall arraying is performed in $O(n)$ time, $O(n^2)$ individual messages, and $O(nD)$ travel distance. Implementation of the sorting and navigation use communication messages of fixed size, and are a practical solution for large populations of low-cost robots.