Parameter Optimization of Cartographer Composition in Fire Rescue Small Apartment Scene

Abstract

When the small-area apartment fires need to be rescued, the original construction drawings cannot be used as a rescue support because of the multi-point reconstruction of the small-area apartment by the residents and the external damage, which requires the unmanned car to quickly obtain the internal environment information. The experimental hardware adopts TS100 tracked damping tank chassis, single-line lidar adopts RPLidarA1 with high stability, and the composition algorithm adopts the cartographer algorithm in laser SLAM. By reducing the number of processing points and increasing the calculation speed and reducing the amount of calculation, the composition parameters of the cartographer with the maximum efficiency of the scanning composition of the small area apartment are obtained. The final adjustment data of the composition parameters are as follows :When the velocity of the robot is 0.5 M / S, the parameter adjustment scheme-HJ-Cartographer is adopted, that is, the optimal value of the maximum iteration number (max_num_iteration) is 12 ; the optimal value of the maximum range of node scanning (max_range) is 29 ; the optimal value of voxel_filter_size is 0.25 ; the optimal number of background threads (MAP_BUILDER_background_threads) of the map generator is 5 ; the optimal value of global_sampling_ratio is 0.0055. The composition accuracy α = 96.77 %, which is 64.83 % higher than the initial composition accuracy. The composition ambiguity β = 3.23 %, which is 92.18 % lower than the initial ambiguity.