Fast and scalable multi-robot deployment planning under connectivity constraints

TL;DR

This paper presents a fast, scalable method for multi-robot deployment planning that ensures connectivity constraints are maintained while reaching multiple goals and dynamically reassigning tasks.

Contribution

It introduces a two-stage approach combining clustering and goal assignment to efficiently coordinate multi-robot deployment under connectivity constraints.

Findings

Effective heuristics for sequential and parallel deployment.

Sub-optimal solutions achieved quickly for large goal sets.

Method scales well with the number of robots and goals.

Abstract

In this paper we develop a method to coordinate the deployment of a multi-robot team to reach some locations of interest, so-called primary goals, and to transmit the information from these positions to a static Base Station (BS), under connectivity constraints. The relay positions have to be established for some robots to maintain the connectivity at the moment in which the other robots visit the primary goals. Once every robot reaches its assigned goal, they are again available to cover new goals, dynamically re-distributing the robots to the new tasks. The contribution of this work is a two stage method to deploy the team. Firstly, clusters of relay and primary positions are computed, obtaining a tree formed by chains of positions that have to be visited. Secondly, the order for optimally assigning and visiting the goals in the clusters is computed. We analyze different heuristics for sequential and parallel deployment in the clusters, obtaining sub-optimal solutions in short time for different number of robots and for a large amount of goals.