Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot

Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhan...
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Autor*in:	Le Huang [verfasserIn] Gongping Wu [verfasserIn] Wenjie Tang [verfasserIn] Yi Wu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 9(2021), Seite 55955-55973
Übergeordnetes Werk:	volume:9 ; year:2021 ; pages:55955-55973

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2021.3070877

Katalog-ID:	DOAJ062158236

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650		4	\|a Transmission lines
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allfields	10.1109/ACCESS.2021.3070877 doi (DE-627)DOAJ062158236 (DE-599)DOAJ026d5268865240559f7fed7b015bdec8 DE-627 ger DE-627 rakwb eng TK1-9971 Le Huang verfasserin aut Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry. Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering Gongping Wu verfasserin aut Wenjie Tang verfasserin aut Yi Wu verfasserin aut In IEEE Access IEEE, 2014 9(2021), Seite 55955-55973 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:9 year:2021 pages:55955-55973 https://doi.org/10.1109/ACCESS.2021.3070877 kostenfrei https://doaj.org/article/026d5268865240559f7fed7b015bdec8 kostenfrei https://ieeexplore.ieee.org/document/9395083/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2021 55955-55973
spelling	10.1109/ACCESS.2021.3070877 doi (DE-627)DOAJ062158236 (DE-599)DOAJ026d5268865240559f7fed7b015bdec8 DE-627 ger DE-627 rakwb eng TK1-9971 Le Huang verfasserin aut Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry. Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering Gongping Wu verfasserin aut Wenjie Tang verfasserin aut Yi Wu verfasserin aut In IEEE Access IEEE, 2014 9(2021), Seite 55955-55973 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:9 year:2021 pages:55955-55973 https://doi.org/10.1109/ACCESS.2021.3070877 kostenfrei https://doaj.org/article/026d5268865240559f7fed7b015bdec8 kostenfrei https://ieeexplore.ieee.org/document/9395083/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2021 55955-55973
allfields_unstemmed	10.1109/ACCESS.2021.3070877 doi (DE-627)DOAJ062158236 (DE-599)DOAJ026d5268865240559f7fed7b015bdec8 DE-627 ger DE-627 rakwb eng TK1-9971 Le Huang verfasserin aut Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry. Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering Gongping Wu verfasserin aut Wenjie Tang verfasserin aut Yi Wu verfasserin aut In IEEE Access IEEE, 2014 9(2021), Seite 55955-55973 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:9 year:2021 pages:55955-55973 https://doi.org/10.1109/ACCESS.2021.3070877 kostenfrei https://doaj.org/article/026d5268865240559f7fed7b015bdec8 kostenfrei https://ieeexplore.ieee.org/document/9395083/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2021 55955-55973
allfieldsGer	10.1109/ACCESS.2021.3070877 doi (DE-627)DOAJ062158236 (DE-599)DOAJ026d5268865240559f7fed7b015bdec8 DE-627 ger DE-627 rakwb eng TK1-9971 Le Huang verfasserin aut Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry. Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering Gongping Wu verfasserin aut Wenjie Tang verfasserin aut Yi Wu verfasserin aut In IEEE Access IEEE, 2014 9(2021), Seite 55955-55973 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:9 year:2021 pages:55955-55973 https://doi.org/10.1109/ACCESS.2021.3070877 kostenfrei https://doaj.org/article/026d5268865240559f7fed7b015bdec8 kostenfrei https://ieeexplore.ieee.org/document/9395083/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2021 55955-55973
allfieldsSound	10.1109/ACCESS.2021.3070877 doi (DE-627)DOAJ062158236 (DE-599)DOAJ026d5268865240559f7fed7b015bdec8 DE-627 ger DE-627 rakwb eng TK1-9971 Le Huang verfasserin aut Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry. Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering Gongping Wu verfasserin aut Wenjie Tang verfasserin aut Yi Wu verfasserin aut In IEEE Access IEEE, 2014 9(2021), Seite 55955-55973 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:9 year:2021 pages:55955-55973 https://doi.org/10.1109/ACCESS.2021.3070877 kostenfrei https://doaj.org/article/026d5268865240559f7fed7b015bdec8 kostenfrei https://ieeexplore.ieee.org/document/9395083/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2021 55955-55973
language	English
source	In IEEE Access 9(2021), Seite 55955-55973 volume:9 year:2021 pages:55955-55973
sourceStr	In IEEE Access 9(2021), Seite 55955-55973 volume:9 year:2021 pages:55955-55973
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification Electrical engineering. Electronics. Nuclear engineering
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container_title	IEEE Access
authorswithroles_txt_mv	Le Huang @@aut@@ Gongping Wu @@aut@@ Wenjie Tang @@aut@@ Yi Wu @@aut@@
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To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. 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callnumber-first	T - Technology
author	Le Huang
spellingShingle	Le Huang misc TK1-9971 misc Transmission lines misc inspection robot misc highlight suppression misc image enhancement misc monocular vision misc parameter modification misc Electrical engineering. Electronics. Nuclear engineering Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot
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topic_title	TK1-9971 Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot Transmission lines inspection robot highlight suppression image enhancement monocular vision parameter modification
topic	misc TK1-9971 misc Transmission lines misc inspection robot misc highlight suppression misc image enhancement misc monocular vision misc parameter modification misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Transmission lines misc inspection robot misc highlight suppression misc image enhancement misc monocular vision misc parameter modification misc Electrical engineering. Electronics. Nuclear engineering
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title	Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot
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title_full	Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot
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title_sort	obstacle distance measurement under varying illumination conditions based on monocular vision using a cable inspection robot
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title_auth	Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot
abstract	Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry.
abstractGer	Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry.
abstract_unstemmed	Obstacle distance measurement is one of the key technologies for autonomous navigation of high-voltage transmission line inspection robots. To address the robustness of obstacle distance measurement under varying illumination conditions, this article develops a research method that fuses image enhancement with robot monocular vision so that the robot can adapt to various levels of illumination running along the transmission line. During the inspection of high-voltage transmission lines in such an overexposed (excessively bright) environment, a specular highlight suppression method is proposed to suppress the specular reflections in an image; when scene illumination is insufficient, a robust low-light image enhancement method based on a tone mapping algorithm with weighted guided filtering is presented. Based on the monocular vision measurement principle, the error generation mechanism is analyzed through experiments, and we introduce the parameter modification mechanism. The two proposed image enhancement methods outperform other state-of-the-art enhancement algorithms in qualitative and quantitative analyses. The experimental results show that the measurement error is less than 3% for static distance measurements and less than 5% for dynamic distance measurements within 6 m. The proposed method can meet the requirements of high-accuracy positioning, real-time performance and strong robustness. This method greatly contributes to the sustainable development of inspection robots in the power industry.
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title_short	Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot
url	https://doi.org/10.1109/ACCESS.2021.3070877 https://doaj.org/article/026d5268865240559f7fed7b015bdec8 https://ieeexplore.ieee.org/document/9395083/ https://doaj.org/toc/2169-3536
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Obstacle Distance Measurement Under Varying Illumination Conditions Based on Monocular Vision Using a Cable Inspection Robot

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