Optimal Distributed Multi-Robot Communication-Aware Trajectory Planning using Alternating Direction Method of Multipliers

TL;DR

This paper introduces a distributed algorithm for multi-robot trajectory planning that optimizes communication and collision avoidance using ADMM, enabling robots to trade communication budgets and coordinate effectively.

Contribution

It proposes a novel distributed optimization framework for communication-aware trajectory planning using ADMM, allowing dynamic budget sharing among robots.

Findings

Effective in simulation for inspection tasks

Ensures communication performance and collision avoidance

Enables dynamic trade-offs in communication budgets

Abstract

This paper presents a distributed, optimal, communication-aware trajectory planning algorithm for multi-robot systems. Building on prior work, it addresses the multi-robot communication-aware trajectory planning problem using a general optimisation framework that imposes linear constraints on changes in robot positions to ensure communication performance and collision avoidance. In this paper, the optimisation problem is solved distributively by separating the communication performance constraint through an economic approach. Here, the current communication budget is distributed equally among the robots, and the robots are allowed to trade parts of their budgets with each other. The separated optimisation problem is then solved using the consensus alternating direction method of multipliers. The method was verified through simulation in an inspection task problem.