Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters

Dynamic Camera Clusters (DCCs) are multi-camera systems where one or more cameras are mounted on actuated mechanisms such as a gimbal. Existing methods for DCC calibration rely on joint angle measurements to resolve the time-varying transformation between the dynamic and static camera. This information is usually provided by motor encoders, however, joint angle measurements are not always readily available on off-the-shelf mechanisms. In this paper, we present an encoderless approach for DCC calibration which simultaneously estimates the kinematic parameters of the transformation chain as well as the unknown joint angles. We also demonstrate the integration of an encoderless gimbal mechanism with a state-of-the art VIO algorithm, and show the extensions required in order to perform simultaneous online estimation of the joint angles and vehicle localization state. The proposed calibration approach is validated both in simulation and on a physical DCC composed of a 2-DOF gimbal mounted on a UAV. Finally, we show the experimental results of the calibrated mechanism integrated into the OKVIS VIO package, and demonstrate successful online joint angle estimation while maintaining localization accuracy that is comparable to a standard static multi-camera configuration.Comment: ICRA 201

Hand-eye calibration for rigid laparoscopes using an invariant point

PURPOSE: Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet it can be difficult due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but one current challenge is in accurate "hand-eye" calibration, which determines the position and orientation of the laparoscope camera relative to the tracking markers. METHODS: In this paper, we propose a simple and clinically feasible calibration method based on a single invariant point. The method requires no additional hardware, can be constructed by theatre staff during surgical setup, requires minimal image processing and can be visualised in real time. Real-time visualisation allows the surgical team to assess the calibration accuracy before use in surgery. In addition, in the laboratory, we have developed a laparoscope with an electromagnetic tracking sensor attached to the camera end and an optical tracking marker attached to the distal end. This enables a comparison of tracking performance. RESULTS: We have evaluated our method in the laboratory and compared it to two widely used methods, "Tsai's method" and "direct" calibration. The new method is of comparable accuracy to existing methods, and we show RMS projected error due to calibration of 1.95 mm for optical tracking and 0.85 mm for EM tracking, versus 4.13 and 1.00 mm respectively, using existing methods. The new method has also been shown to be workable under sterile conditions in the operating room. CONCLUSION: We have proposed a new method of hand-eye calibration, based on a single invariant point. Initial experience has shown that the method provides visual feedback, satisfactory accuracy and can be performed during surgery. We also show that an EM sensor placed near the camera would provide significantly improved image overlay accuracy

Extrinisic Calibration of a Camera-Arm System Through Rotation Identification

Determining extrinsic calibration parameters is a necessity in any robotic system composed of actuators and cameras. Once a system is outside the lab environment, parameters must be determined without relying on outside artifacts such as calibration targets. We propose a method that relies on structured motion of an observed arm to recover extrinsic calibration parameters. Our method combines known arm kinematics with observations of conics in the image plane to calculate maximum-likelihood estimates for calibration extrinsics. This method is validated in simulation and tested against a real-world model, yielding results consistent with ruler-based estimates. Our method shows promise for estimating the pose of a camera relative to an articulated arm's end effector without requiring tedious measurements or external artifacts. Index Terms: robotics, hand-eye problem, self-calibration, structure from motio

Caveats on the first-generation da Vinci Research Kit: latent technical constraints and essential calibrations

Telesurgical robotic systems provide a well established form of assistance in the operating theater, with evidence of growing uptake in recent years. Until now, the da Vinci surgical system (Intuitive Surgical Inc, Sunnyvale, California) has been the most widely adopted robot of this kind, with more than 6,700 systems in current clinical use worldwide [1]. To accelerate research on robotic-assisted surgery, the retired first-generation da Vinci robots have been redeployed for research use as "da Vinci Research Kits" (dVRKs), which have been distributed to research institutions around the world to support both training and research in the sector. In the past ten years, a great amount of research on the dVRK has been carried out across a vast range of research topics. During this extensive and distributed process, common technical issues have been identified that are buried deep within the dVRK research and development architecture, and were found to be common among dVRK user feedback, regardless of the breadth and disparity of research directions identified. This paper gathers and analyzes the most significant of these, with a focus on the technical constraints of the first-generation dVRK, which both existing and prospective users should be aware of before embarking onto dVRK-related research. The hope is that this review will aid users in identifying and addressing common limitations of the systems promptly, thus helping to accelerate progress in the field.Comment: 15 pages, 7 figure