关键词: 巡检机器人, 激光雷达, 改进SLAM, 牧场环境, 定位与建图

Abstract: Aiming at the problems  of low positioning accuracy and robustness, as well as poor precision and stability in mapping for pasture inspection robots, a novel LOMSLAM algorithm based on LiDAR ranging and mapping technology and improved LOMSLAM algorithm is proposed. This algorithm is derived from an enhanced LOAMSLAM algorithm, which integrates laser range finding and surveying technology. LOMSLAM decomposes SLAM into two separate processes such as motion estimation and map construction. By leveraging the high precision of laser range finding and surveying technology, LOMSLAM achieves simultaneous robot localization and map building, thereby enhancing the accuracy, robustness, and stability of both positioning and mapping. LOMSLAM was installed on a designed inspection robot with Mecanum wheel structure for test verification. The results showed that in pose estimation tests, LOMSLAM significantly outperformed other methods in terms of relative pose error (RPE) and absolute trajectory error (ATE), with RMSE values of just 7.28m and 2.23m, respectively, which were lower than the comparative algorithms. In the positioning and mapping tests, with the inspection robot moving at speeds of 0.2 m/s, 0.5 m/s, and 1 m/s, the positioning errors of LOMSLAM were only 0.12 m, 1 m, and 1.2 m, respectively, demonstrating better positioning accuracy and robustness compared to the comparative algorithms.

Key words: inspection robots, LiDAR, improved SLAM, pastoral environment, positioning and mapping