标题： 双目联合相机标定与场景表示 显示英文标题

标题： Bi-Manual Joint Camera Calibration and Scene Representation

摘要： 机器人操作，尤其是双手操作，通常需要在多个机器人操作臂上设置多个摄像头。 在机器人操作臂能够生成运动甚至构建环境表示之前，固定在机器人上的摄像头需要进行校准。 摄像头校准是一个繁琐的过程，涉及收集一组图像，每张图像都捕捉到一个预设的标记。 在这项工作中，我们介绍了双人协作的联合校准与表示框架（Bi-JCR）。 Bi-JCR使每个带有摄像头安装的机器人操作臂能够绕过拍摄校准标记图像的过程。 通过利用三维基础模型进行密集的无标记多视角对应关系，Bi-JCR同时估计：(i) 每个摄像头到其末端执行器的外参变换，(ii) 操作臂之间的相对位姿，以及(iii) 共享工作空间的一个统一且尺度一致的三维表示，所有这些都来自相同的捕获的RGB图像集。 该表示由两个操作臂上的摄像头捕获的图像共同构建，位于公共坐标系中，并支持碰撞检测和语义分割以促进下游双手协作任务。 我们在多种桌面环境中实证评估了Bi-JCR的鲁棒性，并展示了它在各种下游任务中的适用性。 显示英文摘要

摘要： Robot manipulation, especially bimanual manipulation, often requires setting up multiple cameras on multiple robot manipulators. Before robot manipulators can generate motion or even build representations of their environments, the cameras rigidly mounted to the robot need to be calibrated. Camera calibration is a cumbersome process involving collecting a set of images, with each capturing a pre-determined marker. In this work, we introduce the Bi-Manual Joint Calibration and Representation Framework (Bi-JCR). Bi-JCR enables multiple robot manipulators, each with cameras mounted, to circumvent taking images of calibration markers. By leveraging 3D foundation models for dense, marker-free multi-view correspondence, Bi-JCR jointly estimates: (i) the extrinsic transformation from each camera to its end-effector, (ii) the inter-arm relative poses between manipulators, and (iii) a unified, scale-consistent 3D representation of the shared workspace, all from the same captured RGB image sets. The representation, jointly constructed from images captured by cameras on both manipulators, lives in a common coordinate frame and supports collision checking and semantic segmentation to facilitate downstream bimanual coordination tasks. We empirically evaluate the robustness of Bi-JCR on a variety of tabletop environments, and demonstrate its applicability on a variety of downstream tasks.