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

  • Safa ZiadiEmail author
  • Mohamed Njah
  • Sana Charfi
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 270)


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.


Genetic Algorithms Particle Swarm Optimization Mobile robot Path planning 


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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Control and Energy Management Laboratory (CEM-Lab), National Engineering School of SfaxUniversity of SfaxSfaxTunisia
  2. 2.Digital Research Center of Sfax, Technopole of SfaxSfaxTunisia

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