首页|New Robotics Data Have Been Reported by Investigators at Southern University of Science and Technology (SUSTech) (Automatic Extrinsic Calibration for Structured Light Camera and Repetitive Lidars)
New Robotics Data Have Been Reported by Investigators at Southern University of Science and Technology (SUSTech) (Automatic Extrinsic Calibration for Structured Light Camera and Repetitive Lidars)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on Robotics are presented i n a new report. According to news originatingfrom Guangdong, People’s Republic of China, by NewsRx correspondents, research stated, “The integrationof camera and LiDAR technologies has the potential to significantly enhance construction r obots’perception capabilities by providing complementary construction informati on. Structured light cameras(SLCs) are a desirable alternative as they provide comprehensive information on construction defects.”Financial supporters for this research include National Natural Science Foundati on of China (NSFC),Guangdong Natural Science Fund-General Programme, Technology and Innovation Commission of ShenzhenMunicipality.Our news journalists obtained a quote from the research from the Southern Univer sity of Science andTechnology (SUSTech), “However, fusing these two types of in formation depends largely on the sensors’relative positions, which can only be established through extrinsic calibration. This paper introduces anovel calibra tion algorithm considering a customized board for SLCs and repetitive LiDARs, wh ich aredesigned to facilitate the automation of construction robots. The calibr ation board is equipped with foursymmetrically distributed hemispheres, whose c enters are obtained by fitting the spheres and adoptionwith the geometric const raints. Subsequently, the spherical centers serve as reference features to estimate the relationship between the sensors. These distinctive features enable our proposed method to onlyrequire one calibration board pose and minimize human in tervention. We conducted both simulation andreal-world experiments to assess th e performance of our algorithm.”
GuangdongPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsSouthern University of Science and Technology (SUSTech)
NETL
NSTL
