Improvement and Optimization of LVI-SAM Algorithm in Complex Coal Mine Environment
ZHU Xishuo
Abstract：To improve the mapping and navigation capabilities of inspection robots in complex environments such as coal mines,an improved multi-sensor fusion SLAM algorithm was proposed based on the LVI-SAM framework.This algorithm integrates Super4PCS,Iterative Closest Point(ICP),and Normal Distribution Transform(NDT)algorithms into the LIDAR Inertial Subsystem(LIS)of LVI-SAM by introducing a coarse to fine point cloud registration strategy to optimize the attitude estimation process.The simulation results showed that the algorithm supported the robot to autonomously move in more complex simulated coal mines,ensuring the stability of the system in mapping and positioning,and enhancing the navigation ability of the inspection robot in coal mine environments,enabling it to more accurately plan paths and avoid obstacles in complex environments.
Keywords：SLAMmapping and navigationmulti-sensor fusionpoint cloud registrationcoal mine inspection robot
Publication Date：2025-06-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 62-66,70 )