Energy-Optimal Goal Assignment of Multi-Agent System with Goal Trajectories in Polynomials

TL;DR

This paper presents a decentralized method for multi-agent systems to achieve energy-efficient goal assignments with polynomial goal trajectories, ensuring optimal formation with local information.

Contribution

It introduces a novel decentralized optimization framework for goal assignment in multi-agent systems with polynomial trajectories, guaranteeing global optimality.

Findings

The approach minimizes energy consumption for agents reaching goals.

Simulation results validate the effectiveness of the method.

The solution exists globally under polynomial goal trajectories.

Abstract

In this paper, we propose an approach for solving an energy-optimal goal assignment problem to generate the desired formation in multi-agent systems. Each agent solves a decentralized optimization problem with only local information about its neighboring agents and the goals. The optimization problem consists of two sub-problems. The first problem seeks to minimize the energy for each agent to reach certain goals, while the second problem entreats an optimal combination of goal and agent pairs that minimizes the energy cost. By assuming the goal trajectories are given in a polynomial form, we prove the solution to the formulated problem exists globally. Finally, the effectiveness of the proposed approach is validated through the simulation.