This paper presents a novel hybrid motion planning method for holonomic multi-agent systems. The proposed decentralised model predictive control (MPC) framework tackles the intractability of classical centralised MPC for a growing number of agents while providing safety guarantees. This is achieved by combining a decentralised version of the alternating direction method of multipliers (ADMM) with a centralised high-order control barrier function (HOCBF) architecture. Simulation results show significant improvement in scalability over classical centralised MPC. We validate the efficacy and real-time capability of the proposed method by developing a highly efficient C++ implementation and deploying the resulting trajectories on a real industrial magnetic levitation platform.
@article{arxiv.2603.19838,
title = {Multi-Agent Motion Planning on Industrial Magnetic Levitation Platforms: A Hybrid ADMM-HOCBF approach},
author = {Bavo Tistaert and Stan Servaes and Alejandro Gonzalez-Garcia and Ibrahim Ibrahim and Louis Callens and Jan Swevers and Wilm Decré},
journal= {arXiv preprint arXiv:2603.19838},
year = {2026}
}
Comments
8 pages, 4 figures, accepted to the European Control Conference 2026