腹腔鏡手術のペグ移動タスクにおけるロボットの制約付き模倣学習
Robotic Constrained Imitation Learning for the Peg Transfer Task in Fundamentals of Laparoscopic Surgery
腹腔鏡手術の基礎訓練であるペグ移動タスクを、単眼カメラのみを用いた制約付き模倣学習でロボットに実行させる手法を提案し、2台のFranka Emika Pandaで有効性を検証した。
著者: Kento Kawaharazuka, Kei Okada, Masayuki Inaba
分類: cs.RO, cs.AI, cs.LG
原文アブストラクト
In this study, we present an implementation strategy for a robot that performs peg transfer tasks in Fundamentals of Laparoscopic Surgery (FLS) via imitation learning, aimed at the development of an autonomous robot for laparoscopic surgery. Robotic laparoscopic surgery presents two main challenges: (1) the need to manipulate forceps using ports established on the body surface as fulcrums, and (2) difficulty in perceiving depth information when working with a monocular camera that displays its images on a monitor. Especially, regarding issue (2), most prior research has assumed the availability of depth images or models of a target to be operated on. Therefore, in this study, we achieve more accurate imitation learning with only monocular images by extracting motion constraints from one exemplary motion of skilled operators, collecting data based on these constraints, and conducting imitation learning based on the collected data. We implemented an overall system using two Franka Emika Panda Robot Arms and validated its effectiveness.
