Visual-lidar slam based on unsupervised multi-channel deep neural networks

HIGHLIGHTS

  • who: Yi An from the School of Control Science and Engineering, Dalian University of Technology, Dalian, China have published the research: Visual-LiDAR SLAM Based on Unsupervised Multi-channel Deep Neural Networks, in the Journal: (JOURNAL)
  • what: The authors propose a novel unsupervised multi-channel visual-LiDAR SLAM method (MVL-SLAM) which can fuse visual and LiDAR data together. The authors compare the odometry component and SLAM system with other state-of-the art odometry and SLAM methods, such Cognitive Computation 14:1496-1508 as SfMLearner , UndeepVO , UnMono , DeepSLAM , UnGLO , VISO2-Mono, and VISO2-Stereo . . .

     

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