The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods.
The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary hand-eye transformation. We show that it is superior in accuracy and robustness compared to traditional approaches. Second, we decrease the dependency on the calibration object to a single 3D-point by using a similar formulation based on the equation of translation which is much less affected by the estimation error of the calibration object's orientation. Moreover, it makes the estimation of the orientation obsolete while taking advantage of the higher accuracy and robustness from the first solution, resulting in a versatile method for continuous hand-eye calibration.
Towards Robotic Eye Surgery: Marker-free, Online Hand-eye Calibration using Optical Coherence Tomography Images
Technische Universität München（慕尼黑工业大学）；Carl Zeiss Meditec（卡尔蔡司医疗技术公司）；Sun Yat-Sen University（中山大学）；Klinikum rechts der Isar der Technische Universität München（慕尼黑工业大学 Rechts der Isar 医院）
Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；College of Electrical Engineering and Computer Science, Australian National University（澳大利亚国立大学电气工程与计算机科学学院）；College of Engineering, Peking University（北京大学工程学院）
Continual Hand-Eye Calibration for Open-world Robotic Manipulation
School of Automation Science and Engineering, South China University of Technology（华南理工大学自动化科学与工程学院）；State Key Laboratory of Robotics, the Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences（中国科学院机器人研究所）；University of Chinese Academy of Sciences（中国科学院大学）
Kalib: Easy Hand-Eye Calibration with Reference Point Tracking
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（电子信息与电气工程学院，上海交通大学）；Meta Robotics Institute, Shanghai Jiao Tong University（元机器人研究所，上海交通大学）；Qing Yuan Research Institute（青元研究院）；MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University（人工智能联合重点实验室，人工智能学院，上海交通大学）
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）
SurgCalib: Gaussian Splatting-Based Hand-Eye Calibration for Robot-Assisted Minimally Invasive Surgery
Robotics and Control Laboratory, University of British Columbia（机器人与控制实验室，不列颠哥伦比亚大学）；Department of Biomedical Engineering, National University of Singapore（生物医学工程系，新加坡国立大学）；Division of Otolaryngology – Head and Neck Surgery, University of British Columbia（耳鼻喉科–头颈外科部，不列颠哥伦比亚大学）
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）
On-the-fly hand-eye calibration for the da Vinci surgical robot
Department of Mechanical Engineering, Imperial College London（帝国理工学院机械工程系）；Mechatronics in Medicine Laboratory（医学机电实验室）；Hamlyn Centre for Robotics Surgery（机器人外科哈姆林中心）
A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
1 Space \& Terrestrial Autonomous Robotic Systems Laboratory, University of Toronto Institute for Aerospace Studies, Toronto, ON, Canada 2 Institute for Experiential Robotics, Northeastern University, Boston, MA, USA 3 Autonomous Robotics；Convex Optimization Laboratory, McMaster University, Hamilton, ON, Canada
Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis
Humanoid Sensing and Perception, Istituto Italiano di Tecnologia（人机感知与感知，意大利技术研究所）；Rehab Technologies Lab, Istituto Italiano di Tecnologia（康复技术实验室，意大利技术研究所）；DIBRIS, University of Genoa（Genoa大学DIBRIS）
Keep It CALM: Toward Calibration-Free Kilometer-Level SLAM with Visual Geometry Foundation Models via an Assistant Eye
School of Automation and Intelligent Sensing, and Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai Jiao Tong University（自动化与智能感知学院，导航与位置服务上海市重点实验室，上海交通大学）；School of Electrical Engineering and Computer Science, The University of Queensland（电气工程与计算机科学学院，昆士兰大学）；School of Computer Science and Technology, Tongji University（计算机科学与技术学院，同济大学）
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）
