SurgiPose: 単眼手術動画からの手術器具キネマティクス推定による手術ロボット学習
SurgiPose: Estimating Surgical Tool Kinematics from Monocular Video for Surgical Robot Learning
単眼の手術動画から微分可能レンダリングを用いて器具の姿勢と関節角度を推定し、その推定キネマティクスで模倣学習ポリシーを訓練しても実測データと同等の成功率が得られることを示した。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
5. 議論はある?
6. 次に読むべき論文は?
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Juo-Tung Chen, XinHao Chen, Ji Woong Kim, Paul Maria Scheikl, Richard Jaepyeong Cha, Axel Krieger
分類: cs.RO
原文アブストラクト
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.
関連論文
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- dARt Vinci: 手術ロボット学習のための大規模一人称視点データ収集手術ロボット/模倣学習
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- Actor-Criticフレームワークと自己教師あり模倣学習による手術タスク自動化手術ロボット/模倣学習
