Hand-eye calibration, which consists in identifying the rigid- body transformation between a camera mounted on the robot end-effector and the end-effector itself, is a fundamental problem in robot vision. Mathematically, this problem can be formulated as: solve for X in AX = XB. In this paper, we provide a rigorous derivation of the covariance of the solution X, when A and B are randomly perturbed matrices. This fine-grained information is critical for applications that require a high degree of perception precision. Our approach consists in applying covariance propagation methods in SE(3). Experiments involving synthetic and real calibration data confirm that our approach can predict the covariance of the hand-eye transformation with excellent precision.
Foundation Feature-Driven Online End-Effector Pose Estimation: A Marker-Free and Learning-Free Approach
Peking University（北京大学）；Center on Frontiers of Computing Studies, School of Computer Science, Peking University（北京大学计算机科学学院计算前沿研究中心）；PKU-Agibot Lab（北大-星猿哲实验室）；National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University（北京大学计算机科学学院多媒体信息处理国家重点实验室）
In Situ Translational Hand-Eye Calibration of Laser Profile Sensors using Arbitrary Objects
Fondazione Istituto Italiano di Tecnologia（意大利理工学院基金会）；DeepMind；BMW Group（宝马集团）；Danieli Automation S.p.A.（达涅利自动化股份有限公司）；CNR-STIIMA（意大利国家研究委员会-智能工业技术与先进制造研究所）
PlaneHEC: Efficient Hand-Eye Calibration for Multi-view Robotic Arm via Any Point Cloud Plane Detection
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University（国家人类-机器混合增强智能重点实验室，人工智能与机器人研究院，西安交通大学）
Robotic Eye-in-hand Visual Servo Axially Aligning Nasopharyngeal Swabs with the Nasal Cavity
Systems Design Engineering, University of Waterloo（滑铁卢大学系统设计工程系）；Mechanical and Mechatronics Engineering, University of Waterloo（滑铁卢大学机械与机电工程系）；Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院人机学与机器人研究所）
