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Autonomous Needle Manipulation in Robotic Pediatric Surgery Through VR-based AI Training

Research Project

Project/Area Number 25K21581
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 90130:Medical systems-related
Research InstitutionThe University of Tokyo

Principal Investigator

Heredia Saul  東京大学, 大学院医学系研究科(医学部), 助教 (00996788)

Project Period (FY) 2025-04-01 – 2028-03-31
Project Status Granted (Fiscal Year 2025)
Budget Amount *help
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2027: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2026: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2025: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywordsロボットの自律性 / ロボット支援手術 / 機械学習 / 仮想現実シミュレーション / 小児ロボット手術
Outline of Research at the Start

Background: Robotic pediatric surgery is challenging due to limited workspace and delicate tissues.
Purpose: To reduce the surgeon’s burden, we aim to automate needle picking using AI trained in VR.
Plan: Year 1: Improve VR simulator realism and validate with real data. Year 2: Implement and train deep reinforcement learning model in simulation. Year 3: Transfer the model to a real robot and compare its performance to expert surgeons.
Potential impact: Automating repetitive tasks may allow surgeons to focus on critical actions, improving patient outcomes.

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Published: 2025-04-17   Modified: 2025-06-20  

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