The Impact of Mapping Algorithms on Mobile Robot CPU Temperature and Computational Performance

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<ns3:p>This article presents a study on popular algorithms for building 2D and 3D environmental maps using unmanned ground vehicles (UGVs). The research was conducted using a mobile robot integrated with the ROS Noetic platform and equipped with LiDAR, Kinect, and odometry sensors. The robot’s control system implements advanced map generation algorithms based on fusing data from these sensors. The paper first investigates three CPU cooling system configurations for the robot’s onboard computer, analysing their performance under the computational load imposed by the mapping algorithms. Subsequently, the accuracy of specific mapping algorithms (Hector SLAM, GMapping, and RTAB-Map) was evaluated.</ns3:p>