深層強化学習による手術ロボットの半自律制御
Deep Reinforcement Learning Based Semi-Autonomous Control for Robotic Surgery
手術ロボットの反復的な単純操作を自動化するため、深層強化学習を用いた半自律制御フレームワークを提案し、作業時間を19.1%、移動距離を58.7%削減した。
著者: Ruiqi Zhu, Dandan Zhang, Benny Lo
分類: cs.RO, cs.AI
原文アブストラクト
In recent decades, the tremendous benefits surgical robots have brought to surgeons and patients have been witnessed. With the dexterous operation and the great precision, surgical robots can offer patients less recovery time and less hospital stay. However, the controls for current surgical robots in practical usage are fully carried out by surgeons via teleoperation. During the surgery process, there exists a lot of repetitive but simple manipulation, which can cause unnecessary fatigue to the surgeons. In this paper, we proposed a deep reinforcement learning-based semi-autonomous control framework for robotic surgery. The user study showed that the framework can reduce the completion time by 19.1% and the travel length by 58.7%.
関連論文
- RL-MACRO: マルチモーダル適応型ロボット開頭術のためのサイバネティック閉ループ知能フレームワーク手術ロボット/強化学習
- da Vinci Research Kitを用いた強化学習による自律的な手術用灌流・吸引の学習手術ロボット/強化学習
- リーン強化学習によるロボット手術手術ロボット/強化学習
