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CAREER: Human-Centric Control for Teleoperated Surgical Robots

职业：以人为中心的遥控手术机器人控制

基本信息

批准号：
2109635
负责人：
Ann Majewicz Fey
金额：
$ 50万
依托单位：
University of Texas at Austin
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2025-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2109635&HistoricalAwards=false
关键词：
CAREER Human Centric Control Teleoperated

项目摘要

Human-in-the-loop control strategies in which the user performs a task better, and feels more confident to do so, is an important area of research in teleoperated robotics. However, human behavior can often change as a result of environmental, physical, emotional, and social factors. The goal of this Faculty Early Career Development Program (CAREER) project is to design adaptive control systems that can interpret and react to the dynamic human user. This research will be impactful in the field of surgical robotics where interaction with the patient demands safety and effectiveness from both the human operator (surgeon) and the robotic system itself. Robotic systems that are aware and responsive to user skill and performance style could be more able to avoid user errors and respond to adverse events in unpredictable environments. By integrating real-time models of user intent, movement style, and expertise level with a surgical robotic platform, this project will advance the NSF mission to promote the progress of science and advance national health by exploring fundamental relationships human behavior, motor control, and machine manipulation within the context of surgical robotics. The project supports education and broadening participation in engineering by promoting innovation activities related to healthcare and technology development for medical simulation and training. The goal of this CAREER project is to develop adaptive control algorithms for teleoperated robotic surgical systems that can respond to, ignore, and/or augment human motor control inputs depending on the output of user-centric models of behavior and task difficulty. Model output will be based in real-time, data-driven predictions and interpretations of human intent, surgical style, and level of expertise. Research objectives include: developing methods to model and control human behavior (e.g., user behavior and expertise) during unstructured teleoperation tasks; designing and analyzing adaptive control laws to enhance performance through visual and haptic guidance; and evaluating the effectiveness of these algorithms on clinically-relevant outcomes in training and intervention using a surgical robotic platform. A key innovation of this work is designing control methods to be agnostic of the specific task performed by the human operator: only user-centric metrics and movement data will serve as inputs to novel difficulty and stylistic prediction models that will then be used to create adaptive control algorithms. This work could lead to significant improvements in the adaptability, capability, and usability of teleoperated surgical systems when collaborating with a human user.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人机交互控制策略是远程操作机器人研究的一个重要领域，在这种策略中，用户可以更好地执行任务，并且更有信心这样做。然而，人类行为常常会因环境、身体、情感和社会因素而发生变化。该教师早期职业发展计划（CAREER）项目的目标是设计能够解释动态人类用户并做出反应的自适应控制系统。这项研究将对手术机器人领域产生影响，因为与患者的互动需要人类操作员（外科医生）和机器人系统本身的安全性和有效性。意识到并响应用户技能和表现风格的机器人系统可以更好地避免用户错误并在不可预测的环境中响应不良事件。通过将用户意图、运动风格和专业水平的实时模型与手术机器人平台相集成，该项目将通过探索手术机器人背景下的人类行为、运动控制和机器操作的基本关系，推进 NSF 促进科学进步和促进国民健康的使命。该项目通过促进与医疗保健以及医学模拟和培训技术开发相关的创新活动来支持教育和扩大工程参与。该职业项目的目标是为远程操作机器人手术系统开发自适应控制算法，该算法可以根据以用户为中心的行为模型和任务难度的输出来响应、忽略和/或增强人类运动控制输入。模型输出将基于实时、数据驱动的预测和对人类意图、手术风格和专业水平的解释。研究目标包括：开发在非结构化远程操作任务期间建模和控制人类行为（例如用户行为和专业知识）的方法；设计和分析自适应控制法则，以通过视觉和触觉指导提高性能；并评估这些算法对使用手术机器人平台进行训练和干预的临床相关结果的有效性。这项工作的一个关键创新是设计控制方法，使其与人类操作员执行的特定任务无关：只有以用户为中心的指标和运动数据将作为新颖的难度和风格预测模型的输入，然后用于创建自适应控制算法。这项工作在与人类用户合作时可以显着提高远程手术系统的适应性、功能和可用性。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（16）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Online Recognition of Bimanual Coordination Provides Important Context for Movement Data in Bimanual Teleoperated Robots

双手协调的在线识别为双手遥控机器人的运动数据提供了重要的背景

DOI：
发表时间：
2021
期刊：
IEEE International Conference on Robotics and Automation
影响因子：
0
作者：
Boehm, J.;Fey, N.;Majewicz Fey, A.
通讯作者：
Majewicz Fey, A.

A Novel Pulley-Based Simulator for Ureteroscopy with Visuo-Haptic Feedback

具有视觉触觉反馈的新型输尿管镜滑轮模拟器

DOI：
10.1109/haptics52432.2022.9765615
发表时间：
2022
期刊：
Haptics Symposium
影响因子：
0
作者：
Madera, Jonathan;Peters, Craig;Fey, Ann Majewicz
通讯作者：
Fey, Ann Majewicz

Determining the Significant Kinematic Features for Characterizing Stress during Surgical Tasks Using Spatial Attention

使用空间注意力确定手术任务期间表征应力的重要运动学特征

DOI：
10.1142/s2424905x22410069
发表时间：
2022
期刊：
Journal of Medical Robotics Research
影响因子：
0
作者：
Zheng, Yi;Leonard, Grey;Zeh, Herbert;Majewicz Fey, Ann
通讯作者：
Majewicz Fey, Ann

Evaluation of Surgical Performance after Extended Laparoscopic Training using Physical Haptic Constraints

使用物理触觉约束进行扩展腹腔镜训练后的手术表现评估

DOI：
10.1109/biorob52689.2022.9925461
发表时间：
2022
期刊：
BioRob
影响因子：
0
作者：
Wright, Noah;Farr, Deborah;Fey, Ann Majewicz
通讯作者：
Fey, Ann Majewicz

Recognition and Prediction of Surgical Gestures and Trajectories Using Transformer Models in Robot-Assisted Surgery

DOI：
10.1109/iros47612.2022.9981611
发表时间：
2022-10
期刊：
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
影响因子：
0
作者：
Chang Shi;Y. Zheng;A. M. Fey
通讯作者：
Chang Shi;Y. Zheng;A. M. Fey