ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera
A low-cost non-repetitive scanning 3D LiDAR (Light Detection and Ranging) is receiving more attention (the Livox LiDAR). The low cost promotes the large-scale mass-production of various robot systems. Fusing this LiDAR with a thermal camera will improve the perception ability in low illumination...
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| Other Authors: | |
| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/159538 |
| _version_ | 1826128769987903488 |
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| author | Liu, Yiyao |
| author2 | Wang Dan Wei |
| author_facet | Wang Dan Wei Liu, Yiyao |
| author_sort | Liu, Yiyao |
| collection | NTU |
| description | A low-cost non-repetitive scanning 3D LiDAR (Light Detection and Ranging)
is receiving more attention (the Livox LiDAR). The low cost promotes the
large-scale mass-production of various robot systems. Fusing this LiDAR with
a thermal camera will improve the perception ability in low illumination environments.
However, the requirement of large-scale calibration tasks and the
non-uniform scanning pattern poses new challenges. The main difficulty lies in
the automatic detection of the calibration target: i) Most target-based calibration
methods rely on human intervention to detect the target from the point cloud,
but it is inefficient for mass production. ii) Some recently proposed methods
rely on intensity difference to detect the target, but it is not general for different
targets. To solve the problems, ThermalVoxCalib is proposed. The novelties
are: 1) The first research to achieve the calibration between a non-repetitive
scanning 3D LiDAR and a thermal camera. 2) Propose a robust method to automatically
detect a planar target from the point cloud. It can be generalized
to other ranging sensors and other planar targets. 3) We propose to estimate
the extrinsic parameter by minimizing 2D re-projection error, and compare the
accuracy versus minimizing 3D matching error. Quantitative and qualitative experiments
are conducted in both simulation and real environment. Experiments
demonstrate the proposed target detection algorithm is robust and accurate. The
rotation and translation error can reach 0.172° and 0.01m. The 2D re-projection
error can reach 0.58pixels. |
| first_indexed | 2024-10-01T07:30:21Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/159538 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:30:21Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1595382023-07-04T17:44:30Z ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera Liu, Yiyao Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics A low-cost non-repetitive scanning 3D LiDAR (Light Detection and Ranging) is receiving more attention (the Livox LiDAR). The low cost promotes the large-scale mass-production of various robot systems. Fusing this LiDAR with a thermal camera will improve the perception ability in low illumination environments. However, the requirement of large-scale calibration tasks and the non-uniform scanning pattern poses new challenges. The main difficulty lies in the automatic detection of the calibration target: i) Most target-based calibration methods rely on human intervention to detect the target from the point cloud, but it is inefficient for mass production. ii) Some recently proposed methods rely on intensity difference to detect the target, but it is not general for different targets. To solve the problems, ThermalVoxCalib is proposed. The novelties are: 1) The first research to achieve the calibration between a non-repetitive scanning 3D LiDAR and a thermal camera. 2) Propose a robust method to automatically detect a planar target from the point cloud. It can be generalized to other ranging sensors and other planar targets. 3) We propose to estimate the extrinsic parameter by minimizing 2D re-projection error, and compare the accuracy versus minimizing 3D matching error. Quantitative and qualitative experiments are conducted in both simulation and real environment. Experiments demonstrate the proposed target detection algorithm is robust and accurate. The rotation and translation error can reach 0.172° and 0.01m. The 2D re-projection error can reach 0.58pixels. Master of Science (Computer Control and Automation) 2022-06-23T05:35:38Z 2022-06-23T05:35:38Z 2022 Thesis-Master by Coursework Liu, Y. (2022). ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159538 https://hdl.handle.net/10356/159538 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Liu, Yiyao ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title | ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title_full | ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title_fullStr | ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title_full_unstemmed | ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title_short | ThermalVoxCalib: automatic extrinsic calibration between a non-repetitive scanning 3D LiDAR and a thermal camera |
| title_sort | thermalvoxcalib automatic extrinsic calibration between a non repetitive scanning 3d lidar and a thermal camera |
| topic | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics |
| url | https://hdl.handle.net/10356/159538 |
| work_keys_str_mv | AT liuyiyao thermalvoxcalibautomaticextrinsiccalibrationbetweenanonrepetitivescanning3dlidarandathermalcamera |