Ophthalmic microsurgery is known to be a challenging operation, which requires very precise and dexterous manipulation. Image guided robot-assisted surgery is a promising solution that brings significant improvements in outcomes and reduces the physical limitations of human surgeons. However, this technology must be further developed before it can be routinely used in clinics. One of the problems is the lack of proper calibration between the robotic manipulator and appropriate imaging device. In this letter, we developed a flexible framework for hand-eye calibration of an ophthalmic robot with a microscope-integrated optical coherence tomography (OCT) without any markers. The proposed method consists of three main steps are following: First, we estimate the OCT calibration parameters; second, with micro-scale displacements controlled by the robot, we detect and segment the needle tip in three-dimensional OCT volume and; finally, we find the transformation between the coordinate system of the OCT camera and the coordinate system of the robot. We verified the capability of our framework in ex-vivo pig eye experiments and compared the results with a reference method (marker-based). In all experiments, our method showed a small difference from the marker based method, with a mean calibration error of 9.2 μm and 7.0 μm, respectively. Additionally, the noise test shows the robustness of the proposed method.
Hand-eye calibration is an active research topic in robotics and has been investigated by many researchers. In particular, the seminal work of since 1980s @cite_5 . There exist several off-the-shelf calibration solutions that implement Tsai's method (e.g. ViSP library @cite_25 , which is designed for visual servoing applications). These existing off-the-shelf calibration solutions can be easily integrated into standard camera vision systems and allow fast prototyping. However, they require separate measurements and extra equipment (calibration grids, markers,...). In some medical scenarios, it is not practical to place the calibration objects or markers inside the tissue or bodily organ. In addition, medical imaging modalities (e.g OCT and ultrasound) have different imaging principles, which leads to a different camera calibration process.
@cite_5 @cite_25
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The authors describe a novel technique for computing position and orientation of a camera relative to the last joint of a robot manipulator in an eye-on-hand configuration. It takes only about 100+64N arithmetic operations to compute the hand eye relationship after the robot finishes the movement, and incurs only additional 64 arithmetic operations for each additional station. The robot makes a series of automatically planned movements with a camera rigidly mounted at the gripper. At the end of each move, it takes a total of 90 ms to grab an image, extract image feature coordinates, and perform camera extrinsic calibration. After the robot finishes all the movements, it takes only a few milliseconds to do the calibration. A series of generic geometric properties or lemmas are presented, leading to the derivation of the final algorithms, which are aimed at simplicity, efficiency, and accuracy while giving ample geometric and algebraic insights. Critical factors influencing the accuracy are analyzed, and procedures for improving accuracy are introduced. Test results of both simulation and real experiments on an IBM Cartesian robot are reported and analyzed. > ViSP (Visual Servoing Platform), a fully functional modular architecture that allows fast development of visual servoing applications, is described. The platform takes the form of a library which can be divided in three main modules: control processes, canonical vision-based tasks that contain the most classical linkages, and real-time tracking. ViSP software environment features independence with respect to the hardware, simplicity, extendibility, and portability. ViSP also features a large library of elementary tasks with various visual features that can be combined together, an image processing library that allows the tracking of visual cues at video rate, a simulator, an interface with various classical framegrabbers, a virtual 6-DOF robot that allows the simulation of visual servoing experiments, etc. The platform is implemented in C++ under Linux.