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arXiv · 2610.10065

Distributed Motion Planning for Multi-Robot Systems under Topological Constraints

Abstract

Efficient and distributed coordination of mobile robots is one of the main challenges in multi-robot systems. Topological constraints, often expressed as topological braids, are a popular tool to encode complex coordination patterns between multiple mobile robots, as they offer a compact and abstract representation of the desired qualitative relation between the space-time trajectories of the robots. However, execution of joint motion plans encoded as braid-based topological constraints via distributed controllers is challenging, with existing approaches, generally based on the execution of one braid generator at a time, producing slow and suboptimal trajectories. We propose a distributed controller based on Model Predictive Control (MPC) to efficiently execute braid-based topological specifications. Rather than directly tracking the braid specification, we propose to use winding numbers, which are topological invariants for braids, as a proxy. This has the twofold benefit of converting braids into a continuous function, which can be easily tracked by an MPC controller through an appropriate term in the cost function, and of decoupling the global braid specification into a set of pairwise specifications, which can be tracked distributedly through the solution of only local MPC problems. To maintain global coordination, we propose a consensus-based progress estimation approach, which allows the robots to synchronize their motion toward the desired specification. We validate the proposed approach in simulation and in real-world experiments, where we demonstrate the effectiveness of the proposed approach and the improvement over existing approaches in terms of execution speed and control effort.

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BibTeXRIS

Gianpietro Battocletti, Dimitris Boskos, Dimos V. Dimarogonas, Bart De Schutter. 2026-10-07. Distributed Motion Planning for Multi-Robot Systems under Topological Constraints. https://arxiv.org/abs/2610.10065

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