Laser & Optoelectronics Progress, Volume. 62, Issue 12, 1215011(2025)

Self-Supervised Learning-Based Camera-Radar Odometry Fusion Localization

Hanwen Zhang1 and Yanyang Wang1,2、*
Author Affiliations
  • 1Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu 610039, China
  • 2Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan, Xihua University, Chengdu 610039, China
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    Figures & Tables(8)
    Overall network architecture of the GAE
    General structure of visual odometry
    Structures of CDC module and LGFI module
    Differentiable view reconstruction process of radar frames
    Structure of FusionNet
    Comparison of depth prediction results of three algorithms
    Oxford Radar RobotCar dataset test trajectories
    • Table 1. Trajectory errors of various algorithms in Oxford Radar RobotCar sequences

      View table

      Table 1. Trajectory errors of various algorithms in Oxford Radar RobotCar sequences

      AlgorithmSequence
      18-14-1418-14-4618-15-20Mean16-14-15(rain)
      GRAMME(camera)8.74/1.528.11/1.4910.54/5.229.13/2.7411.04/1.62
      Proposed algorithm(camera)9.15/1.648.83/1.538.61/1.818.86/1.669.72/2.14
      GRAMME1.57/0.110.74/0.150.92/0.251.08/0.172.85/0.36
      Proposed algorithm1.32/0.130.71/0.100.39/0.250.81/0.161.58/0.32
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    Hanwen Zhang, Yanyang Wang. Self-Supervised Learning-Based Camera-Radar Odometry Fusion Localization[J]. Laser & Optoelectronics Progress, 2025, 62(12): 1215011

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    Paper Information

    Category: Machine Vision

    Received: Sep. 3, 2024

    Accepted: Jan. 7, 2025

    Published Online: Jun. 25, 2025

    The Author Email: Yanyang Wang (yywang@mail.xhu.edu.cn)

    DOI:10.3788/LOP241942

    CSTR:32186.14.LOP241942

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