SurgiPose：从单目视频估计手术工具运动学以实现手术机器人学习
SurgiPose: Estimating Surgical Tool Kinematics from Monocular Video for Surgical Robot Learning
AI总结：
SurgiPose通过单目视频估计手术工具运动学，为手术机器人学习提供可行的解决方案，验证了无需真实运动学数据即可训练有效策略的可行性。
摘要：
模仿学习（IL）在实现自主灵巧操作方面展现出了巨大潜力，包括学习手术任务。为了充分释放IL在手术中的潜力，需要访问临床数据集，但不幸的是，这些数据集缺乏当前IL方法所需的运动学数据。一个有前途的大型手术演示来源是在线可用的单目手术视频，因此单目姿态估计成为实现大规模机器人学习的关键步骤。为此，我们提出了SurgiPose，一种基于可微渲染的方法，用于从单目手术视频中估计运动学信息，从而消除了直接访问真实运动学数据的需要。我们的方法通过优化工具姿态参数来推断工具轨迹和关节角度，以最小化渲染图像与真实图像之间的差异。为了评估我们方法的有效性，我们在两个机器人手术任务上进行了实验：组织提升和针吸取，使用da Vinci Research Kit Si（dVRK Si）。我们使用真实测量的运动学数据和从视频中估计的运动学数据训练模仿学习策略，并比较其性能。我们的结果表明，使用估计的运动学数据训练的策略在成功率上与使用真实数据训练的策略相当，证明了基于单目视频的运动学估计在手术机器人学习中的可行性。通过使单目手术视频能够估计运动学，我们的工作为从在线手术数据中学习自主手术策略奠定了基础。
英文摘要：
Imitation learning (IL) has shown immense promise in enabling autonomous dexterous manipulation, including learning surgical tasks. To fully unlock the potential of IL for surgery, access to clinical datasets is needed, which unfortunately lack the kinematic data required for current IL approaches. A promising source of large-scale surgical demonstrations is monocular surgical videos available online, making monocular pose estimation a crucial step toward enabling large-scale robot learning. Toward this end, we propose SurgiPose, a differentiable rendering based approach to estimate kinematic information from monocular surgical videos, eliminating the need for direct access to ground truth kinematics. Our method infers tool trajectories and joint angles by optimizing tool pose parameters to minimize the discrepancy between rendered and real images. To evaluate the effectiveness of our approach, we conduct experiments on two robotic surgical tasks: tissue lifting and needle pickup, using the da Vinci Research Kit Si (dVRK Si). We train imitation learning policies with both ground truth measured kinematics and estimated kinematics from video and compare their performance. Our results show that policies trained on estimated kinematics achieve comparable success rates to those trained on ground truth data, demonstrating the feasibility of using monocular video based kinematic estimation for surgical robot learning. By enabling kinematic estimation from monocular surgical videos, our work lays the foundation for large scale learning of autonomous surgical policies from online surgical data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
