• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment
【2h】

Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment

机译：基于GICP的强大3D LiDAR SLAM适用于地下采矿环境

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Unmanned mining is one of the most effective methods to solve mine safety and low efficiency. However, it is the key to accurate localization and mapping for underground mining environment. A novel graph simultaneous localization and mapping (SLAM) optimization method is proposed, which is based on Generalized Iterative Closest Point (GICP) three-dimensional (3D) point cloud registration between consecutive frames, between consecutive key frames and between loop frames, and is constrained by roadway plane and loop. GICP-based 3D point cloud registration between consecutive frames and consecutive key frames is first combined to optimize laser odometer constraints without other sensors such as inertial measurement unit (IMU). According to the characteristics of the roadway, the innovative extraction of the roadway plane as the node constraint of pose graph SLAM, in addition to automatic removing the noise point cloud to further improve the consistency of the underground roadway map. A lightweight and efficient loop detection and optimization based on rules and GICP is designed. Finally, the proposed method was evaluated in four scenes (such as the underground mine laboratory), and compared with the existing 3D laser SLAM method (such as Lidar Odometry and Mapping (LOAM)). The results show that the algorithm could realize low drift localization and point cloud map construction. This method provides technical support for localization and navigation of underground mining environment.
机译：无人采矿是解决矿山安全和低效率的最有效方法之一。但是，这是对地下采矿环境进行精确定位和制图的关键。提出了一种新颖的图同时定位与映射优化方法，该方法基于连续帧之间，连续关键帧之间以及循环帧之间的广义迭代最近点（GICP）三维（3D）点云配准，并且受巷道平面和环路的约束。首先将连续帧和连续关键帧之间基于GICP的3D点云配准进行组合，以优化激光里程表约束，而无需其他传感器，例如惯性测量单元（IMU）。根据巷道的特点，除了自动去除噪声点云以进一步提高地下巷道图的一致性外，还创新性地提取了巷道平面作为姿态图SLAM的节点约束。设计了基于规则和GICP的轻量级高效循环检测和优化。最后，在四个场景（例如地下矿井实验室）中对所提出的方法进行了评估，并与现有的3D激光SLAM方法（例如激光雷达测距和制图（LOAM））进行了比较。结果表明，该算法可以实现低漂移定位和点云图的构建。该方法为地下采矿环境的定位和导航提供了技术支持。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号