Laser & Optoelectronics Progress, Volume. 58, Issue 3, 3280041(2021)

LiDAR Real-Time Detection of Tunnel Centerline Based on Particle Swarm Optimization Algorithm

Wang Yanglang1, Wang Kewei1,2, and Zou Bin1,2、*
Author Affiliations
  • 1Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan , Hubei 430070, China
  • 2Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan , Hubei 430070, China
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    This paper proposed a real-time detection method for tunnel centerline by 16-line LiDAR based on particle swarm optimization (PSO) algorithm to solve too narrow of the beam''s two sides from the tunnel wall crossing the tunnel. We designed a three-dimensional LiDAR bracket for a certain type of beam truck, installed and calibrated the LiDAR, and constructed a real-time tunnel-center-detection platform for the beam transport vehicle. Using the PSO algorithm and point cloud filtering (PCL) in the point cloud library, we processed the LiDAR data and then calculated the real-time cross-swing angle of the vehicle''s forward direction relative to the vertical tunnel. Thus, we obtained the point cloud of the tunnel wall''s cross section and fitted the center point coordinate and radius of the circle using the PSO algorithm to fit the tunnel centerline. The experimental results show that the method can effectively detect the tunnel centerline. The errors between the tunnel radius calculated by this method and the actual tunnel radius and between the extracted tunnel centerline and actual tunnel centerline were both within 3 cm. Hence, the proposed method can effectively detect real-time tunnel centerline.

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    Wang Yanglang, Wang Kewei, Zou Bin. LiDAR Real-Time Detection of Tunnel Centerline Based on Particle Swarm Optimization Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(3): 3280041

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jun. 16, 2020

    Accepted: --

    Published Online: Mar. 12, 2021

    The Author Email: Bin Zou (1173059950@qq.com)

    DOI:10.3788/LOP202158.0328004

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