220 / 2023-09-27 00:20:30
Multi-source fusion positioning algorithm of ROS robot platform based on improved LVI-SAM
Underground complex environment;,improved LVI-SAM,multi-source fusion
Abstract Pending
星星 肖 / 北京建筑大学 测绘与城市空间学院


The rapid acquisition of surrounding environmental information for the carrier is crucial for achieving accurate and robust positioning in underground spaces. This study focuses on optimizing the fusion of lidar, vision, and inertial navigation using the LVI-SAM algorithm to achieve robust positioning of the ROS robot platform in underground spaces. The proposed method enhances visual initialization by utilizing imu node data prediction, improves visual depth estimation with laser data, enhances the interaction of node data information by providing bias initial estimates for the imu through vision, and constructs a closed-loop factor using the global pose map to facilitate algorithm optimization. Experimental results demonstrate that the optimized algorithm effectively reduces positioning translation errors and enables high-precision and robust acquisition of position information in the underground complex field environment for the ROS robot platform.
Important Date
  • Conference Date

    Oct 26

    2023

    to

    Oct 29

    2023

  • Oct 15 2023

    Abstract Submission Deadline

  • Oct 15 2023

    Draft paper submission deadline

  • Nov 13 2023

    Registration deadline

Sponsored By
International Society for Mine Surveying
China Coal Society
China Surveying and Mapping Society
Organized By
中国矿业大学
中国煤炭科工集团有限公司