Research on Underground Coal Mine Map Construction Method Based on LeGO-LOAM Improved Algorithm
نویسندگان
چکیده
The application of intelligent equipment and technologies such as robots unmanned vehicles is an important part the construction mines, has become China’s national coal energy development strategy consensus industry. Environment perception instant positioning one key destined to realize autonomous navigation in underground simultaneous location mapping (SLAM) effective method deploying this technology. space a mine long narrow, environment complex changeable, structure irregular, lighting poor. This typical unstructured environment, which poses great challenge SLAM. paper summarizes current research status map based on visual SLAM Lidar SLAM, analyzes defects LeGO-LOAM algorithm, loopback detection errors or omissions. We use SegMatch improve module LeGO-LOAM, iterative closest point (ICP) algorithm optimize global map, then propose improved namely LeGO-LOAM-SM, describe its principle implementation. performance LeGO-LOAM-SM was also tested using KITTI dataset 00 sequence experimental data collected two simulation scenarios, indexes effect, trajectory overlap length deviation, absolute error (ATE), relative pose (RPE) were analyzed. results show that constructed by clearer, better estimated smoother more accurate, translation rotation accuracy approximately 5%. can construct accurate cloud low drift position estimation, verifies effectiveness algorithm. Finally, satisfy requirements, two-dimensional occupancy grid studied, test carried out. raster effectively filter out outlier noise dynamic obstacles, 0.01 m, required storage compared with reduced three orders magnitude. enrich implementation environments help solve problems perception, real-time positioning, vehicles.
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ژورنال
عنوان ژورنال: Energies
سال: 2022
ISSN: ['1996-1073']
DOI: https://doi.org/10.3390/en15176256