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Integration of N-GCPSO Algorithm with Spatial Particle Extension Algorithm for Multi-Robot Search

Hafidlotul F. Ahmad, Hendradi Hardhienata, Karlisa Priandana

Year
2020
Citations
5

Abstract

This paper considers multi-robot search problems where a group of robots must discover and allocate themselves to targets. To solve this problem, we embed the robot with an algorithm called the Neighborhood with the Guaranteed Convergence Particle Swarm Optimization (N-GCPSO). This study considers the problem in a simulation environment. To reduce collision between robots, we integrate the N-GCPSO algorithm with a spatial particle extension algorithm. Simulation results show that the integration of N-GCPSO with a spatial partial extension algorithm increases the effectiveness of N-GCPSO by reducing the number of collisions between robots without reducing its performance in discovering and allocating targets.

Keywords

Extension (predicate logic)RobotAlgorithmComputer scienceConvergence (economics)Particle swarm optimizationMathematical optimizationArtificial intelligenceMathematics

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