Mobile Robot Localization Based on the PSO Algorithm with Local Minima Avoiding the Fitness Function.

ABSTRACT: 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

SUBMITTER: Bratina B 

PROVIDER: S-EPMC12567416 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature