arXiv:2503.08214cs.ROcs.SY2025-03中稿 · publication in IEE…被引 2

用安全约束确保内镜机器人切割肿瘤时不伤周围组织。

Safety-Ensured Robotic Control Framework for Cutting Task Automation in Endoscopic Submucosal Dissection

  • 基于控制屏障函数,精准识别邻近肿瘤边界。
  • 无需动力学模型,在复杂环境下仍能保障操作安全。
  • 适合临床内镜手术自动化研究者参考。

近年来,利用机器人系统自动化外科任务(如内镜治疗胃肠道癌症)受到广泛关注。然而,以往研究多集中于目标检测与分析,对安全性关注不足,而安全性在临床应用中至关重要,因不当机器人运动可能引发事故。本文提出一种新的控制框架,通过端口内镜机器人实现内镜黏膜下剥离术(ESD)中切割任务的自动化,并形式化保证安全性。该框架采用控制屏障函数(CBFs)精确识别相邻肿瘤边界,即使在胃肠道内紧密分布的情况下也能确保精准切除并保护正常组织。此外,采用无模型控制方案,使安全性保障在动态建模困难的内镜机器人系统中依然可行。我们在仿真环境中验证了该框架,针对多个邻近肿瘤进行切除实验,结果表明安全约束被有效执行:机器人可完全移除目标肿瘤且不损伤邻近肿瘤。

原文摘要 · Abstract (English)

There is growing interest in automating surgical tasks using robotic systems, such as endoscopy for treating gastrointestinal (GI) cancer. However, previous studies have primarily focused on detecting and analyzing objects or robots, with limited attention to ensuring safety, which is critical for clinical applications, where accidents can be caused by unsafe robot motions. In this study, we propose a new control framework that can formally ensure the safety of automating the cutting task in endoscopic submucosal dissection (ESD), a representative endoscopic surgical method for the treatment of early GI cancer, by using an endoscopic robot. The proposed framework utilizes Control Barrier Functions (CBFs) to accurately identify the boundaries of individual tumors, even in close proximity within the GI tract, ensuring precise treatment and removal while preserving the surrounding normal tissue. Additionally, by adopting a model-free control scheme, safety assurance is made possible even in endoscopic robotic systems where dynamic modeling is challenging. We demonstrate the proposed framework in a simulation-based experimental environment, where the tumors to be removed are close to each other, and show that the safety constraints are enforced. We show that the model-free CBF-based controlled robot eliminates one tumor completely without damaging it, while not invading another nearby tumor.

内镜手术机器人控制安全约束肿瘤切除

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