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Updated: Jan 18, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Published on: October 14, 2017

Development of a Dynamic Path Planning System for Autonomous Mobile Robots Using a Multi-Agent System Approach.

Bradley Fourie¹, Louis Louw¹, Günter Bitsch²

¹Department of Industrial Engineering, Stellenbosch University, Stellenbosch 7600, South Africa.

Sensors (Basel, Switzerland)

|September 13, 2025

Summary

This summary is machine-generated.

This study presents a dynamic path planning system for Autonomous Mobile Robots (AMRs) in Industry 4.0 Flexible Manufacturing Systems (FMS). The novel approach ensures efficient, conflict-free navigation for multiple AMRs in dynamic environments.

Keywords:

Autonomous Mobile Robots (AMRs)Flexible Manufacturing Systems (FMS)Multi-Agent Systems (MAS)dynamic path planning

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Area of Science:

Robotics and Automation
Artificial Intelligence
Industrial Engineering

Background:

Industry 4.0 relies on Autonomous Mobile Robots (AMRs) for intralogistics.
Flexible Manufacturing Systems (FMS) present dynamic challenges for AMR path planning.
Scalable, decentralized solutions are needed for multi-AMR conflict management.

Purpose of the Study:

To develop a dynamic path planning system for AMRs in FMS.
To enable reactive adaptation to disturbances and generalization across layouts.
To integrate multi-AMR conflict avoidance within a decentralized architecture.

Main Methods:

A Multi-Agent Systems (MAS) architecture with software AMR agents.
A hybrid Genetic Algorithm (GA) using Cell-Based Decomposition (CBD) for path optimization.
The Iterative Exclusion Principle (IEP) for multi-AMR conflict avoidance, including Predictive Collision Avoidance (PCA).

Main Results:

Successful deadlock avoidance for up to nine AMRs with good scalability.
Robust adaptation to static and dynamic obstacles in simulated FMS.
Stable run times and consistent path quality demonstrated.

Conclusions:

The hybrid GA and MAS-based approach is feasible for dynamic AMR control in complex industrial settings.
The system effectively manages multiple AMRs and avoids conflicts in FMS.
This research contributes to efficient and reliable intralogistics in Industry 4.0.