Laser SLAM research for mobile energy storage and charging robots

With the rapid development of electric vehicles, the limitations of traditional fixed located charging stations are gradually highlighted, mobile energy storage charging robots have a wide range of application scenarios and markets. SLAM technology for mapping the environment is one of the important technologies in the field of mobile robotics. Selecting suitable algorithms is crucial for mobile energy storage charging robots to get more accurate environment maps and achieve autonomous navigation, obstacle avoidance and other functions. In this paper, based on Robot Operating System(ROS) system, three laser SLAM algorithms, Fast-Lio, Gmapping and Cartographer, are proposed to run in simulation environment and real scenario, and the maps generated by them are evaluated. The experimental and evaluation results demonstrate the successful map creation capability of all three algorithms. In comparison, Cartographer exhibits superior robustness and generates more comprehensive maps that closely align with the ground truth map. Consequently, Cartographer is better suited for large-scale and complicated scenarios.