Controlling robotic manipulators via visual feedback requires a known coordinate frame transformation between the robot and the camera. Uncertainties in mechanical systems as well as camera calibration create errors in this coordinate frame transformation. These errors result in poor localization of robotic manipulators and create a significant challenge for applications that rely on precise interactions between manipulators and the environment. In this work, we estimate the camera-to-base transform and joint angle measurement errors for surgical robotic tools using an image based insertion-shaft detection algorithm and probabilistic models. We apply our proposed approach in both a structured environment as well as an unstructured environment and measure to demonstrate the efficacy of our methods.

翻译：通过视觉反馈控制机器人操作臂需要已知机器人相机与相机之间的坐标系变换。机械系统的不确定性以及相机标定会导致该坐标系变换产生误差。这些误差会造成机器人操作臂定位不准确，对依赖操作臂与环境精确交互的应用构成重大挑战。本研究提出采用基于图像的插入杆检测算法与概率模型，估计手术机器人器械的相机-基座变换矩阵及关节角度测量误差。我们在结构化环境与非结构化环境中分别验证所提出方法，通过实验测量证明其有效性。