Research on Two-Round Self-Balancing Robot SLAM Based on the Gmapping Algorithm

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 5; p. 2489
• Main Authors: Zhao, Jianwei, Li, Jinyu, Zhou, Jiaxin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.02.2023; MDPI
• Subjects: Algorithms; Carbon fibers; Carbon steel; Coal industry; Coal mining; Composite materials; Deformation; Design; Design and construction; Gmapping algorithm; Inspection; Load; Localization; Location-based systems; PID controller; R&D; Research & development; Robots; Safety and security measures; Simulation; SLAM; two-wheel self-balancing robot; China; PID controller; SLAM; Gmapping algorithm; two-wheel self-balancing robot
• DOI: 10.3390/s23052489
• ISSN: 1424-8220

Aiming at the inconvenience of inspection and monitoring of coal mine pump room equipment in a narrow and complex environment, this paper proposes and designs a two-wheel self-balancing inspection robot based on laser SLAM. Using SolidWorks, the three-dimensional mechanical structure of the robot is designed, and the overall structure of the robot is analyzed by finite element statics. The kinematics model of the two-wheel self-balancing robot was established, and the multi-closed-loop PID controller was used to design the two-wheel self-balancing control algorithm of the robot. The 2D LiDAR-based Gmapping algorithm was used to locate the robot and construct the map. Through the self-balancing test and anti-jamming test, it is verified that the self-balancing algorithm designed in this paper has a certain anti-jamming ability and good robustness. By using Gazebo to build a simulation comparison experiment, it is verified that the selection of the particle number is of great significance for improving the map accuracy. The actual test results show that the constructed map has high accuracy.