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Particle Swarm Optimization-Based Framework for 3D Swarm Robotic Navigation Using Artificial Potential Field Dynamics

Authors :

Samim Kamyab¹ Masoud Shirzadeh² Ghoncheh Zand³

1- University of Tehran 2- (Tehran Polytechnic) Amirkabir University of Technology 3- (Tehran Polytechnic) Amirkabir University of Technology

Keywords :

artificial potential field،particle swarm optimization،swarm robotics

Abstract :

This paper presents a framework based on the Particle Swarm Optimization (PSO) algorithm for three-dimensional (3D) swarm robotic navigation using enhanced Artificial Potential Field (APF) dynamics. The proposed method automatically adjusts key navigation parameters to improve navigation performance in terms of time to goal, collision avoidance, energy efficiency, and collective coordination. Simulation results show that the PSO-APF approach significantly reduces the number of collisions, ensures collective coordinated convergence, and keeps energy consumption within the optimal range, compared with classical APF methods. This framework is scalable, computationally efficient, and capable of real-time implementation, and has high potential for practical 3D swarm robotic applications.

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