A Co-simulation framework using MATLAB and CoppeliaSim for path planning of nonholonomic mobile robots

Simulation plays a vital role in the design, testing, and validation of autonomous mobile robot navigation systems, particularly when real-world experimentation is constrained by cost, safety, or logistical limitations. This paper presents a modular and scalable co-simulation framework integrating MATLAB and CoppeliaSim for the path planning of nonholonomic wheeled mobile robots in static environments. The framework leverages MATLAB’s computational and fuzzy logic capabilities for controller development, while CoppeliaSim provides a physics-based 3D simulation environment for modeling robot kinematics, sensing, and interaction with obstacles. Communication between the two platforms is achieved via the CoppeliaSim Remote API, enabling real-time data exchange for closed-loop control. The system supports dynamic sensor feedback, customizable fuzzy inference systems, and visual monitoring of robot behavior. To validate the framework, a case study involving a fuzzy logic controller for obstacle avoidance was conducted, with performance evaluated based on traversal time and path efficiency. Results demonstrate that the framework provides a reliable, flexible, and low-cost alternative to physical prototyping for early-stage development and testing of autonomous navigation algorithms.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17759288
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

A Co-simulation framework using MATLAB and CoppeliaSim for path planning of nonholonomic mobile robots

Zenodo (CERN European Organization for Nuclear Research)
Robotic Path Planning Algorithms
article

A Co-simulation framework using MATLAB and CoppeliaSim for path planning of nonholonomic mobile robots

article en

Abstract

Simulation plays a vital role in the design, testing, and validation of autonomous mobile robot navigation systems, particularly when real-world experimentation is constrained by cost, safety, or logistical limitations. This paper presents a modular and scalable co-simulation framework integrating MATLAB and CoppeliaSim for the path planning of nonholonomic wheeled mobile robots in static environments. The framework leverages MATLAB’s computational and fuzzy logic capabilities for controller development, while CoppeliaSim provides a physics-based 3D simulation environment for modeling robot kinematics, sensing, and interaction with obstacles. Communication between the two platforms is achieved via the CoppeliaSim Remote API, enabling real-time data exchange for closed-loop control. The system supports dynamic sensor feedback, customizable fuzzy inference systems, and visual monitoring of robot behavior. To validate the framework, a case study involving a fuzzy logic controller for obstacle avoidance was conducted, with performance evaluated based on traversal time and path efficiency. Results demonstrate that the framework provides a reliable, flexible, and low-cost alternative to physical prototyping for early-stage development and testing of autonomous navigation algorithms.

Zenodo (CERN European Organization for Nuclear Research)
Maseno University (KE), Technical University of Mombasa (KE)
Openalex Percentile: Top 40%
Robotic Path Planning Algorithms
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