Mobile robots have broad market application prospects in modern integrated intelligent manufacturing due to their advantages such as reliable performance and reduced manufacturing costs.However,there exist problems such as single perception dimension,low precision in the indoor environment perception system of mobile robots,which is hard to meet the demands of multi-dimensional real-time and accurate perception of the environment at pres-ent.Therefore,an environment perception system that could simultaneously perform 2D dynamic target detection and 3D scene map reconstruction in a laboratory environment was constructed by simulating a logistics warehouse,the images collected by the binocular camera were respectively input into the improved You Only Look Once version 3(YOLOv3)network fused with Tree-structured Feature Aggregation(TFA)module and the optimized RTAB-MAP algorithm with Multi-Scale Retinex with Color Restoration(MSRCR)algorithm and key frame filtering mech-anism,thus the results were displayed in Robot Visualization tool(RVIZ)in real time and achieved multi-dimen-sional environment perception,so that it could meet the needs of multi-tasking.The experimental results showed that the precision and recall in dynamic target detection were improved by 1.78％and 1.73％respectively compared with the original algorithm,the detection time was 16.57ms/f,and the average positioning error was 1.49％.Com-pared with the original algorithm,the errors of the improved RTAB-MAP algorithm were significantly reduced,and the quality of the 3D point cloud map in the actual indoor scene reconstruction was better.
维普
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