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Which is Better for Mobile Robot Trajectory Optimization: PSO or GA?

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New Trends in Robot Control

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 270))

Abstract

In mobile robot research domain and especially in its path planning sub-domain, the optimization tools the most used are PSO (Particle Swarm Optimization) and GA (Genetic Algorithms). In fact, mobile robot path planning is a multi-objective optimization problem where at least these objectives are considered: the shortest and the safest path to the goal. Sometimes other objectives are added like travel duration. The subject of this paper is a comparison investigation concerning the efficiency of PSO and GA in mobile robot path planning optimization. We start with a comparison of evolutionary performances of PSO and GA. Then, we apply PSO and GA in the optimization of parameters of DVSF\(^{2}\) (Dynamic Variable Speed Force Field) path planning approach. Different environments of different types, statics and dynamics are considered in these simulations to decide which is better for mobile robot path planning optimization: PSO or GA.

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Authors and Affiliations

  1. Control and Energy Management Laboratory (CEM-Lab), National Engineering School of Sfax, University of Sfax, Sfax, Tunisia

    Safa Ziadi & Mohamed Njah

  2. Digital Research Center of Sfax, Technopole of Sfax, Sfax, Tunisia

    Safa Ziadi, Mohamed Njah & Sana Charfi

Authors
  1. Safa Ziadi
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  2. Mohamed Njah
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  3. Sana Charfi
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Corresponding author

Correspondence to Safa Ziadi .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Sultan Qaboos University, Al Khoudh, Oman

    Jawhar Ghommam

  2. National School of Engineers of Sfax, University of Sfax, Sfax, Tunisia

    Nabil Derbel

  3. Department of Engineering Design and Mathematics, University of the West of England, Bristol, UK

    Quanmin Zhu

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Ziadi, S., Njah, M., Charfi, S. (2020). Which is Better for Mobile Robot Trajectory Optimization: PSO or GA?. In: Ghommam, J., Derbel, N., Zhu, Q. (eds) New Trends in Robot Control. Studies in Systems, Decision and Control, vol 270. Springer, Singapore. https://doi.org/10.1007/978-981-15-1819-5_13

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