ORIGINAL RESEARCH article
Front. Control Eng.
Sec. Control and Automation Systems
Volume 6 - 2025 | doi: 10.3389/fcteg.2025.1645918
This article is part of the Research TopicField Applications of Advanced Process Control, Real-Time Optimization, Expert Systems and Decision Support SystemsView all articles
Conflict-based Model Predictive Control for Multi-agent Path Finding - Experimentally Validated on a Magnetic Planar Drive System
Provisionally accepted
Kai Janning1*
Abdalsalam Housin1Christopher Schulte2
Frederik Erkens1Luca Frenken1
Laura Herbst1
Bastian Nießing1
Robert Schmitt3- 1Fraunhofer Institute for Production Technology (FHG), Aachen, Germany
- 2Rheinisch-Westfalische Technische Hochschule Aachen Lehrstuhl und Institut fur Regelungstechnik, Aachen, Germany
- 3Chair of Intelligence in Quality Sensing, Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Aachen, Germany
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This work presents an approach to collision avoidance in multi-agent systems (MAS) by integrating Conflict-Based Search (CBS) with Model Predictive Control (MPC), referred to as Conflict-Based Model Predictive Control (CB-MPC). The proposed method leverages the conflict-avoidance strengths of CBS to generate collision-free paths, which are then refined into dynamic reference trajectories using a minimum jerk trajectory optimizer and then used inside a MPC to follow the trajectories and to avoid collisions. This integration ensures real-time trajectory execution, preventing collisions and adapting to online changes. The approach is evaluated using a magnetic planar drive system for realistic multi-agent scenarios, demonstrating enhanced real-time responsiveness and adaptability. The focus is on the development of a motion planning algorithm and its validation in dynamic environments, which are becoming increasingly relevant in modern adaptive production sites. On the MAS demonstrator with four active agents, ten different scenarios were created with varying degrees of complexity in terms of route planning. In addition, external disturbances that hinder the execution of the paths were simulated. All calculation and solution times were recorded and discussed. The result show that all scenarios could be successfully solved and executed, and the CB-MPC is therefore suitable for motion planning on the presented MAS demonstrator. The greatest limitation of the approach lies in scalability with regard to increasing the number of agents.
Keywords: Conflict-based search, model predictive control, multi-agent coordination, path planning, collision avoidance, sequential quadratic programming, Planar drive, Automation
Received: 12 Jun 2025; Accepted: 09 Jul 2025.
Copyright: © 2025 Janning, Housin, Schulte, Erkens, Frenken, Herbst, Nießing and Schmitt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kai Janning, Fraunhofer Institute for Production Technology (FHG), Aachen, Germany
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