Extrinsic calibration between thermal camera and mmWave radar for intelligent robots
LiDAR (Light Detection And Ranging) and RGB (Red-Green-Blue) camera perform well in general condition while 4D mmWave Radar (RAdio Detection And Ranging) and thermal camera do better in harsh environment. 4D Radar and thermal camera data fusion futher benefits intelligent robots to be used in variou...
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| Formáid: | Thesis-Master by Coursework |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
Nanyang Technological University
2022
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| Ábhair: | |
| Rochtain ar líne: | https://hdl.handle.net/10356/159546 |
| _version_ | 1826122351907962880 |
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| author | Zhang, Shini |
| author2 | Wang Dan Wei |
| author_facet | Wang Dan Wei Zhang, Shini |
| author_sort | Zhang, Shini |
| collection | NTU |
| description | LiDAR (Light Detection And Ranging) and RGB (Red-Green-Blue) camera perform well in general condition while 4D mmWave Radar (RAdio Detection And Ranging) and thermal camera do better in harsh environment. 4D Radar and thermal camera data fusion futher benefits intelligent robots to be used in various scenarios. There were limited literatures about these two sensors fusion as it was not long after the 4D Radar is pushed into market. Moreover, due to the heterogeneity of the two sensors, common feature is the main difficulty of the calibration. To solve these problems, 4DRadar2ThermalCalib is proposed.
The three main contributions of this dissertation are: 1) A systematic intrinsic and extrinsic calibration method, 4DRadar2ThermalCalib, for a 4D mmWave Radar and a thermal camera is proposed. 2) A novel calibration target, sphericaltrihedral, is designed to provide the common features between a 4D mmWave
Radar and a thermal camera. 3) Sphere center features in both Radar point cloud data and thermal image data are detected automatically.
The results of the extrinsic calibration is obtained by minimizing the re-projection error. Both quantitative and qualitative analysis are implemented to prove that the 4DRadar2ThermalCalib method performs well in real environment. The overall re-projection error is 1.88 pixels. |
| first_indexed | 2024-10-01T05:47:06Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/159546 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:47:06Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1595462023-07-04T17:44:11Z Extrinsic calibration between thermal camera and mmWave radar for intelligent robots Zhang, Shini Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics LiDAR (Light Detection And Ranging) and RGB (Red-Green-Blue) camera perform well in general condition while 4D mmWave Radar (RAdio Detection And Ranging) and thermal camera do better in harsh environment. 4D Radar and thermal camera data fusion futher benefits intelligent robots to be used in various scenarios. There were limited literatures about these two sensors fusion as it was not long after the 4D Radar is pushed into market. Moreover, due to the heterogeneity of the two sensors, common feature is the main difficulty of the calibration. To solve these problems, 4DRadar2ThermalCalib is proposed. The three main contributions of this dissertation are: 1) A systematic intrinsic and extrinsic calibration method, 4DRadar2ThermalCalib, for a 4D mmWave Radar and a thermal camera is proposed. 2) A novel calibration target, sphericaltrihedral, is designed to provide the common features between a 4D mmWave Radar and a thermal camera. 3) Sphere center features in both Radar point cloud data and thermal image data are detected automatically. The results of the extrinsic calibration is obtained by minimizing the re-projection error. Both quantitative and qualitative analysis are implemented to prove that the 4DRadar2ThermalCalib method performs well in real environment. The overall re-projection error is 1.88 pixels. Master of Science (Computer Control and Automation) 2022-06-24T01:25:03Z 2022-06-24T01:25:03Z 2022 Thesis-Master by Coursework Zhang, S. (2022). Extrinsic calibration between thermal camera and mmWave radar for intelligent robots. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159546 https://hdl.handle.net/10356/159546 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Zhang, Shini Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title | Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title_full | Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title_fullStr | Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title_full_unstemmed | Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title_short | Extrinsic calibration between thermal camera and mmWave radar for intelligent robots |
| title_sort | extrinsic calibration between thermal camera and mmwave radar for intelligent robots |
| topic | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics |
| url | https://hdl.handle.net/10356/159546 |
| work_keys_str_mv | AT zhangshini extrinsiccalibrationbetweenthermalcameraandmmwaveradarforintelligentrobots |