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Assessing Path Planning Algorithms of Mobile Robots: A ROS-Based Simulation Framework

In: Disruptive Technologies and Optimization Towards Industry 4.0 Logistics

Author

Listed:
  • Georgios Karamitsos

    (International Hellenic University)

  • Dimitrios Bechtsis

    (International Hellenic University)

  • Naoum Tsolakis

    (International Hellenic University)

  • Dimitrios Vlachos

    (Aristotle University of Thessaloniki)

Abstract

The increasing use of mobile robots in diverse working environments (e.g., manufacturing, logistics, agriculture) for supporting and executing material handling and labor-intensive operations necessitates path planning techniques. Path planning algorithms shall calculate the optimal route and navigate a mobile robot to ensure optimal performance in terms of travel time, distance, and required computational resources. In particular, path planning algorithms shall be flexible to accommodate miscellaneous operational spaces and ensure a mobile robot’s optimal yet collision-free routing. However, integrated software applications that encompass a set of path planning algorithms while offering flexibility and simplicity for direct implementation to real-work settings are lacking. In this respect, this research aims to: (a) provide a critical taxonomy of common path planning approaches; and (b) develop a bespoke software implementation using the ROS framework to allow path planning algorithm’s performance assessment in both cyberspace and real-world equivalent environments. The study results showcase the effectiveness of the elaborated path planning algorithms and the usefulness of the developed software application for comparatively assessing alternative routing options.

Suggested Citation

  • Georgios Karamitsos & Dimitrios Bechtsis & Naoum Tsolakis & Dimitrios Vlachos, 2024. "Assessing Path Planning Algorithms of Mobile Robots: A ROS-Based Simulation Framework," Springer Optimization and Its Applications, in: Athanasia Karakitsiou & Athanasios Migdalas & Panos M. Pardalos (ed.), Disruptive Technologies and Optimization Towards Industry 4.0 Logistics, pages 139-160, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-58919-5_5
    DOI: 10.1007/978-3-031-58919-5_5
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