Heuristic Planner for Communication-Constrained Multi-Agent Multi-Goal Path Planning

TL;DR

This paper introduces a graph-search algorithm for multi-agent multi-goal path planning in robotics, ensuring communication constraints are maintained while minimizing total completion time.

Contribution

It presents a novel heuristic planner that coordinates multiple robots' paths considering communication constraints and multiple goals, improving over existing methods.

Findings

Paths maintain communication constraints throughout the mission.

The algorithm effectively minimizes total completion time.

Agents coordinate for current and future goals seamlessly.

Abstract

In robotics, coordinating a group of robots is an essential task. This work presents the communication-constrained multi-agent multi-goal path planning problem and proposes a graph-search based algorithm to address this task. Given a fleet of robots, an environment represented by a weighted graph, and a sequence of goals, the aim is to visit all the goals without breaking the communication constraints between the agents, minimizing the completion time. The resulting paths produced by our approach show how the agents can coordinate their individual paths, not only with respect to the next goal but also with respect to all future goals, all the time keeping the communication within the fleet intact.