深層強化学習制御による消化管内ナビゲーション用移動型磁気マニピュレーションプラットフォーム
A Mobile Magnetic Manipulation Platform for Gastrointestinal Navigation with Deep Reinforcement Learning Control
UR5ロボットアームに4電磁石アレイを搭載した小型・低コストな移動型磁気操作システムを構築し、Sim-to-Realパイプラインで訓練したSACベースの深層強化学習制御により、7mmの磁気カプセルを2D軌道上で高精度に追従させた。
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著者: Zhifan Yan, Chang Liu, Yiyang Jiang, Wenxuan Zheng, Xinhao Chen, Axel Krieger
分類: cs.RO
原文アブストラクト
Targeted drug delivery in the gastrointestinal (GI) tract using magnetic robots offers a promising alternative to systemic treatments. However, controlling these robots is a major challenge. Stationary magnetic systems have a limited workspace, while mobile systems (e.g., coils on a robotic arm) suffer from a "model-calibration bottleneck", requiring complex, pre-calibrated physical models that are time-consuming to create and computationally expensive. This paper presents a compact, low-cost mobile magnetic manipulation platform that overcomes this limitation using Deep Reinforcement Learning (DRL). Our system features a compact four-electromagnet array mounted on a UR5 collaborative robot. A Soft Actor-Critic (SAC)-based control strategy is trained through a sim-to-real pipeline, enabling effective policy deployment within 15 minutes and significantly reducing setup time. We validated the platform by controlling a 7-mm magnetic capsule along 2D trajectories. Our DRL-based controller achieved a root-mean-square error (RMSE) of 1.18~mm for a square path and 1.50~mm for a circular path. We also demonstrated successful tracking over a clinically relevant, 30 cm * 20 cm workspace. This work demonstrates a rapidly deployable, model-free control framework capable of precise magnetic manipulation in a large workspace,validated using a 2D GI phantom.
関連論文
- 安定な2次元磁気トラップのための永久磁石アレイの効率的最適化磁気マニピュレーション
- 磁気カプセル内視鏡のための軌道計画と制御磁気マニピュレーション
