OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving
Accurate sensor calibration is a prerequisite for multi-sensor perception and localization systems for autonomous vehicles. The intrinsic parameter calibration of the sensor is to obtain the mapping relationship inside the sensor, and the extrinsic parameter calibration is to transform two or more s...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , |
|---|---|
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Yan, Guohang Zhuochun, Liu Wang, Chengjie Shi, Chunlei Wei, Pengjin Cai, Xinyu Ma, Tao Liu, Zhizheng Zhong, Zebin Liu, Yuqian Zhao, Ming Ma, Zheng Li, Yikang |
| description | Accurate sensor calibration is a prerequisite for multi-sensor perception and
localization systems for autonomous vehicles. The intrinsic parameter
calibration of the sensor is to obtain the mapping relationship inside the
sensor, and the extrinsic parameter calibration is to transform two or more
sensors into a unified spatial coordinate system. Most sensors need to be
calibrated after installation to ensure the accuracy of sensor measurements. To
this end, we present OpenCalib, a calibration toolbox that contains a rich set
of various sensor calibration methods. OpenCalib covers manual calibration
tools, automatic calibration tools, factory calibration tools, and online
calibration tools for different application scenarios. At the same time, to
evaluate the calibration accuracy and subsequently improve the accuracy of the
calibration algorithm, we released a corresponding benchmark dataset. This
paper introduces various features and calibration methods of this toolbox. To
our knowledge, this is the first open-sourced calibration codebase containing
the full set of autonomous-driving-related calibration approaches in this area.
We wish that the toolbox could be helpful to autonomous driving researchers. We
have open-sourced our code on GitHub to benefit the community. Code is
available at https://github.com/PJLab-ADG/SensorsCalibration. |
| doi_str_mv | 10.48550/arxiv.2205.14087 |
| format | Article |
| fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2205_14087</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2205_14087</sourcerecordid><originalsourceid>FETCH-LOGICAL-a677-218a0590c366b9cca49ac8e4a8e179d5e293f26e413b1ae7f2f777b2871ee6cf3</originalsourceid><addsrcrecordid>eNotz7tOwzAYhmEvDKhwAUz4BhJ8PrBFKSepqEv26LdrV5bSuHKSqtw9EJg-6R0-6UHogZJaGCnJE5RrutSMEVlTQYy-Rdv9OYwtDMk94wZ_LsOcqimMUy54rQXmlEfc5Ty4fMXxpzfLnMd8ysuEtyVd0ni8QzcRhinc_-8Gda8vXfte7fZvH22zq0BpXTFqgEhLPFfKWe9BWPAmCDCBanuQgVkemQqCckch6Mii1toxo2kIyke-QY9_tyujP5d0gvLV_3L6lcO_ASsRRUk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving</title><source>arXiv.org</source><creator>Yan, Guohang ; Zhuochun, Liu ; Wang, Chengjie ; Shi, Chunlei ; Wei, Pengjin ; Cai, Xinyu ; Ma, Tao ; Liu, Zhizheng ; Zhong, Zebin ; Liu, Yuqian ; Zhao, Ming ; Ma, Zheng ; Li, Yikang</creator><creatorcontrib>Yan, Guohang ; Zhuochun, Liu ; Wang, Chengjie ; Shi, Chunlei ; Wei, Pengjin ; Cai, Xinyu ; Ma, Tao ; Liu, Zhizheng ; Zhong, Zebin ; Liu, Yuqian ; Zhao, Ming ; Ma, Zheng ; Li, Yikang</creatorcontrib><description>Accurate sensor calibration is a prerequisite for multi-sensor perception and
localization systems for autonomous vehicles. The intrinsic parameter
calibration of the sensor is to obtain the mapping relationship inside the
sensor, and the extrinsic parameter calibration is to transform two or more
sensors into a unified spatial coordinate system. Most sensors need to be
calibrated after installation to ensure the accuracy of sensor measurements. To
this end, we present OpenCalib, a calibration toolbox that contains a rich set
of various sensor calibration methods. OpenCalib covers manual calibration
tools, automatic calibration tools, factory calibration tools, and online
calibration tools for different application scenarios. At the same time, to
evaluate the calibration accuracy and subsequently improve the accuracy of the
calibration algorithm, we released a corresponding benchmark dataset. This
paper introduces various features and calibration methods of this toolbox. To
our knowledge, this is the first open-sourced calibration codebase containing
the full set of autonomous-driving-related calibration approaches in this area.
We wish that the toolbox could be helpful to autonomous driving researchers. We
have open-sourced our code on GitHub to benefit the community. Code is
available at https://github.com/PJLab-ADG/SensorsCalibration.</description><identifier>DOI: 10.48550/arxiv.2205.14087</identifier><language>eng</language><subject>Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Robotics</subject><creationdate>2022-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,777,882</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2205.14087$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2205.14087$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Yan, Guohang</creatorcontrib><creatorcontrib>Zhuochun, Liu</creatorcontrib><creatorcontrib>Wang, Chengjie</creatorcontrib><creatorcontrib>Shi, Chunlei</creatorcontrib><creatorcontrib>Wei, Pengjin</creatorcontrib><creatorcontrib>Cai, Xinyu</creatorcontrib><creatorcontrib>Ma, Tao</creatorcontrib><creatorcontrib>Liu, Zhizheng</creatorcontrib><creatorcontrib>Zhong, Zebin</creatorcontrib><creatorcontrib>Liu, Yuqian</creatorcontrib><creatorcontrib>Zhao, Ming</creatorcontrib><creatorcontrib>Ma, Zheng</creatorcontrib><creatorcontrib>Li, Yikang</creatorcontrib><title>OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving</title><description>Accurate sensor calibration is a prerequisite for multi-sensor perception and
localization systems for autonomous vehicles. The intrinsic parameter
calibration of the sensor is to obtain the mapping relationship inside the
sensor, and the extrinsic parameter calibration is to transform two or more
sensors into a unified spatial coordinate system. Most sensors need to be
calibrated after installation to ensure the accuracy of sensor measurements. To
this end, we present OpenCalib, a calibration toolbox that contains a rich set
of various sensor calibration methods. OpenCalib covers manual calibration
tools, automatic calibration tools, factory calibration tools, and online
calibration tools for different application scenarios. At the same time, to
evaluate the calibration accuracy and subsequently improve the accuracy of the
calibration algorithm, we released a corresponding benchmark dataset. This
paper introduces various features and calibration methods of this toolbox. To
our knowledge, this is the first open-sourced calibration codebase containing
the full set of autonomous-driving-related calibration approaches in this area.
We wish that the toolbox could be helpful to autonomous driving researchers. We
have open-sourced our code on GitHub to benefit the community. Code is
available at https://github.com/PJLab-ADG/SensorsCalibration.</description><subject>Computer Science - Computer Vision and Pattern Recognition</subject><subject>Computer Science - Robotics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz7tOwzAYhmEvDKhwAUz4BhJ8PrBFKSepqEv26LdrV5bSuHKSqtw9EJg-6R0-6UHogZJaGCnJE5RrutSMEVlTQYy-Rdv9OYwtDMk94wZ_LsOcqimMUy54rQXmlEfc5Ty4fMXxpzfLnMd8ysuEtyVd0ni8QzcRhinc_-8Gda8vXfte7fZvH22zq0BpXTFqgEhLPFfKWe9BWPAmCDCBanuQgVkemQqCckch6Mii1toxo2kIyke-QY9_tyujP5d0gvLV_3L6lcO_ASsRRUk</recordid><startdate>20220527</startdate><enddate>20220527</enddate><creator>Yan, Guohang</creator><creator>Zhuochun, Liu</creator><creator>Wang, Chengjie</creator><creator>Shi, Chunlei</creator><creator>Wei, Pengjin</creator><creator>Cai, Xinyu</creator><creator>Ma, Tao</creator><creator>Liu, Zhizheng</creator><creator>Zhong, Zebin</creator><creator>Liu, Yuqian</creator><creator>Zhao, Ming</creator><creator>Ma, Zheng</creator><creator>Li, Yikang</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20220527</creationdate><title>OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving</title><author>Yan, Guohang ; Zhuochun, Liu ; Wang, Chengjie ; Shi, Chunlei ; Wei, Pengjin ; Cai, Xinyu ; Ma, Tao ; Liu, Zhizheng ; Zhong, Zebin ; Liu, Yuqian ; Zhao, Ming ; Ma, Zheng ; Li, Yikang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a677-218a0590c366b9cca49ac8e4a8e179d5e293f26e413b1ae7f2f777b2871ee6cf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Computer Vision and Pattern Recognition</topic><topic>Computer Science - Robotics</topic><toplevel>online_resources</toplevel><creatorcontrib>Yan, Guohang</creatorcontrib><creatorcontrib>Zhuochun, Liu</creatorcontrib><creatorcontrib>Wang, Chengjie</creatorcontrib><creatorcontrib>Shi, Chunlei</creatorcontrib><creatorcontrib>Wei, Pengjin</creatorcontrib><creatorcontrib>Cai, Xinyu</creatorcontrib><creatorcontrib>Ma, Tao</creatorcontrib><creatorcontrib>Liu, Zhizheng</creatorcontrib><creatorcontrib>Zhong, Zebin</creatorcontrib><creatorcontrib>Liu, Yuqian</creatorcontrib><creatorcontrib>Zhao, Ming</creatorcontrib><creatorcontrib>Ma, Zheng</creatorcontrib><creatorcontrib>Li, Yikang</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yan, Guohang</au><au>Zhuochun, Liu</au><au>Wang, Chengjie</au><au>Shi, Chunlei</au><au>Wei, Pengjin</au><au>Cai, Xinyu</au><au>Ma, Tao</au><au>Liu, Zhizheng</au><au>Zhong, Zebin</au><au>Liu, Yuqian</au><au>Zhao, Ming</au><au>Ma, Zheng</au><au>Li, Yikang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving</atitle><date>2022-05-27</date><risdate>2022</risdate><abstract>Accurate sensor calibration is a prerequisite for multi-sensor perception and
localization systems for autonomous vehicles. The intrinsic parameter
calibration of the sensor is to obtain the mapping relationship inside the
sensor, and the extrinsic parameter calibration is to transform two or more
sensors into a unified spatial coordinate system. Most sensors need to be
calibrated after installation to ensure the accuracy of sensor measurements. To
this end, we present OpenCalib, a calibration toolbox that contains a rich set
of various sensor calibration methods. OpenCalib covers manual calibration
tools, automatic calibration tools, factory calibration tools, and online
calibration tools for different application scenarios. At the same time, to
evaluate the calibration accuracy and subsequently improve the accuracy of the
calibration algorithm, we released a corresponding benchmark dataset. This
paper introduces various features and calibration methods of this toolbox. To
our knowledge, this is the first open-sourced calibration codebase containing
the full set of autonomous-driving-related calibration approaches in this area.
We wish that the toolbox could be helpful to autonomous driving researchers. We
have open-sourced our code on GitHub to benefit the community. Code is
available at https://github.com/PJLab-ADG/SensorsCalibration.</abstract><doi>10.48550/arxiv.2205.14087</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.48550/arxiv.2205.14087 |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_arxiv_primary_2205_14087 |
| source | arXiv.org |
| subjects | Computer Science - Computer Vision and Pattern Recognition Computer Science - Robotics |
| title | OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T14%3A40%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=OpenCalib:%20A%20Multi-sensor%20Calibration%20Toolbox%20for%20Autonomous%20Driving&rft.au=Yan,%20Guohang&rft.date=2022-05-27&rft_id=info:doi/10.48550/arxiv.2205.14087&rft_dat=%3Carxiv_GOX%3E2205_14087%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |