20.500.12556/DKUM-95739 Mobile robot localization based on the PSO algorithm with local minima avoiding the fitness function Localization of a semi-humanoid mobile robot Pepper is proposed based on the particle swarm optimization algorithm (PSO) that is robust to the disturbance perturbations of LIDAR-measured distances from the mobile robot to the walls of the robot real laboratory workspace. The novel PSO, with the avoiding local minima algorithm (PSO-ALM), uses a novel fitness function that can prevent the PSO search from trapping into the local minima and thus prevent the mobile robot from misidentifying the actual location. The fitness function penalizes nonsense solutions by introducing continuous integrity checks of solutions between two different consecutive locations. The proposed methodology enables accurate and real-time global localization of a mobile robot, given the underlying a priori map, with a consistent and predictable time complexity. Numerical simulations and real-world laboratory experiments with different a priori map accuracies have been conducted to prove the proper functioning of the method. The results have been compared with the benchmarks, i.e., the plain vanilla PSO and the built-in robot’s odometrical method, a genetic algorithm with included elitism and adaptive mutation rate (GA), the same GA algorithm with the included ALM algorithm (GA-ALM), the state-of-the-art plain vanilla golden eagle optimization (GEO) algorithm, and the same GEO algorithm with the added ALM algorithm (GEO-ALM). The results showed similar performance with the odometrical method right after recalibration and significantly better performance after some traveled distance. The GA and GEO algorithms with or without the ALM extension gave us similar results according to the accuracy of localization. The optimization algorithms’ performance with added ALM algorithms was much better at not getting caught in the local minimum, while the PSO-ALM algorithm gave us the overall best results mobile robot localization PSO algorithm avoid the global minima lokalizacija mobilnega robota algoritmi PSO true false true MDPI Angleški jezik Slovenski jezik https://www.mdpi.com/journal/sensors © 2025 by the authors Članek v reviji 2025-10-17 12:41:37 2025-10-17 12:41:38 2025-10-18 03:21:14 0000-00-00 00:00:00 2025 0 0 28 str. iss. 20, [article no.] 6283 Vol. 25 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-08-18 2025-09-18 2025-10-10 681.5 253582339 10.3390/s25206283 1424-8220 sensors-25-06283-v3.pdf sensors-25-06283-v3.pdf 1 835612A4E063647AF5EEEEB62A00E8EF b034b636327ab1f88fc2859ba909e35e27146b6fb313580b5901b500638c9494 3a060f35-ab46-11f0-a0a8-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=199967 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0