NRI: INT: Collaborative Research: ForceBot: Customizable Robotic Platform for Body-Scale Physical Interaction Simulation in Virtual Reality

NRI：INT：协作研究：ForceBot：虚拟现实中人体规模物理交互模拟的可定制机器人平台

• 批准号: 2024784
• 负责人: Jing Du
• 金额: $ 31.3万
• 依托单位: University of Florida
• 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 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024784&HistoricalAwards=false
• 关键词: NRI; INT; Collaborative; Research; ForceBot

This National Robotics Initiative project will contribute new knowledge at the convergence of several fields: virtual reality, robotic control, sensory feedback, ergonomics, and human factors. A customizable cobot will be designed to increase the fidelity of virtual reality simulations. The system will enable a user to feel the physical forces, movements, and constraints at both hands and both feet. By integrating a "whole-body" robotic system with a virtual reality platform, the PIs will advance the understanding of how robotics can be used to identify potential risks of human worker / robot collaborations, and for training towards reducing workplace risk exposures. The PIs will use modeling and simulation to evaluate and remove potential hazards to humans from collaborative robotic operations as well as to test collaborative robot and human interactions using simulated test beds. The effectiveness of the system will be evaluated via perceived presence, behavioral, and neurophysiological analysis. The project will advance the national prosperity by benefitting industry sectors that are likely to deploy collaborative robots (e.g., agriculture, construction, and healthcare). This project will benefit society by accelerating, through simulation, safety hazards that may arise when new technology is being designed, even before it gets deployed in the physical world. In addition, the PIs will engage a diverse pool of graduate and undergraduate students in the research. Project activities also include mentoring of high school students with disabilities to college and STEM training for first-generation elementary school students from rural areas through robotics summer camps. This project will design, build, control, and assess the effectiveness of a body-scale physical interaction simulation cobot in Virtual Reality that provides customizable force and position feedback at the hands and feet. The platform (named ForceBot) is a novel cobot designed to dramatically increase the fidelity of virtual reality simulations. This project will significantly contribute to the field of human-robot interaction by exploring how robot-based active haptic simulation can adapt to a variety of tasks, environments, and people, with minimal modification to hardware and software. Project effort is organized into three objectives: development of techniques for haptic rendering of simulated interactions using a VR physics engine; implementing and controlling the ForceBot system; and evaluating the integrated system in a series of human subject experiments. The project will advance knowledge of robot dynamics and algorithms for personalized human motion recognition and prediction. ForceBot will enable workers to receive training on future work, identifying potential risks of collaborative robots to workers, and evaluation of different control strategies for wearable robots like exoskeletons. If successful, this research will expand the potential for using virtual reality for training intensive physical tasks in multiple application domains including sports, gaming, emergency response, and industrial applications for reducing workplace risk exposures.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.

该国家机器人计划项目将在多个领域的融合中贡献新知识：虚拟现实、机器人控制、感官反馈、人体工程学和人为因素。可定制的协作机器人将被设计来提高虚拟现实模拟的保真度。该系统将使用户能够感受到双手和双脚的物理力量、运动和约束。通过将“全身”机器人系统与虚拟现实平台相集成，PI 将加深对机器人技术如何用于识别人类工人/机器人协作的潜在风险以及如何进行减少工作场所风险暴露的培训的理解。 PI 将使用建模和仿真来评估和消除协作机器人操作对人类的潜在危害，并使用模拟测试台测试协作机器人和人类的交互。该系统的有效性将通过感知存在、行为和神经生理学分析来评估。该项目将使可能部署协作机器人的行业（例如农业、建筑和医疗保健）受益，从而促进国家繁荣。该项目将通过模拟加速新技术设计时（甚至在其部署到物理世界之前）可能出现的安全隐患，从而造福社会。此外，PI 还将吸引多元化的研究生和本科生参与研究。项目活动还包括指导残疾高中生上大学，以及通过机器人夏令营为来自农村地区的第一代小学生提供 STEM 培训。该项目将设计、构建、控制和评估虚拟现实中人体规模的物理交互模拟协作机器人的有效性，该机器人可在手部和脚部提供可定制的力和位置反馈。该平台（名为 ForceBot）是一种新颖的协作机器人，旨在显着提高虚拟现实模拟的保真度。该项目将探索基于机器人的主动触觉模拟如何在对硬件和软件进行最小修改的情况下适应各种任务、环境和人员，从而为人机交互领域做出重大贡献。项目工作分为三个目标：开发使用 VR 物理引擎进行模拟交互的触觉渲染的技术；实施和控制 ForceBot 系统；并在一系列人体实验中评估集成系统。该项目将增进机器人动力学和个性化人体运动识别和预测算法的知识。 ForceBot将使工人能够接受未来工作的培训，识别协作机器人对工人的潜在风险，并评估外骨骼等可穿戴机器人的不同控制策略。 如果成功，这项研究将扩大使用虚拟现实在多个应用领域训练密集体力任务的潜力，包括体育、游戏、应急响应和工业应用，以减少工作场所风险暴露。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来获得支持。

项目成果

Robot-Assisted Immersive Kinematic Experience Transfer for Welding Training

用于焊接培训的机器人辅助沉浸式运动学经验转移

• DOI: 10.1061/jccee5.cpeng-5138
• 发表时间: 2023-03
• 期刊: Journal of Computing in Civil Engineering
• 影响因子: 6.9
• 作者: Ye, Yang;Zhou, Tianyu;Du, Jing
• 通讯作者: Du, Jing

Exoskeleton Training through Haptic Sensation Transfer in Immersive Virtual Environment

在沉浸式虚拟环境中通过触觉感觉传递进行外骨骼训练

• DOI: 10.1061/9780784483961.059
• 发表时间: 2022-03
• 期刊: ASCE Construction Research Congress (CRC
• 作者: Ye, Yang;Shi, Yangming;Lee, Youngjae;Burks, Garret;Srinivasan, Divya;Du, Jing
• 通讯作者: Du, Jing

Robot Planning for Active Collision Avoidance in Modular Construction: Pipe Skids Example

模块化建筑中主动避免碰撞的机器人规划：管道滑移示例

• DOI: 10.1061/(asce)co.1943-7862.0002374
• 发表时间: 2022-10
• 期刊: Journal of Construction Engineering and Management
• 影响因子: 5.1
• 作者: Zhu, Qi;Zhou, Tianyu;Xia, Pengxiang;Du, Jing
• 通讯作者: Du, Jing

Neurobehavioral assessment of force feedback simulation in industrial robotic teleoperation

工业机器人远程操作中力反馈模拟的神经行为评估

• DOI: 10.1016/j.autcon.2021.103674
• 发表时间: 2021-06
• 期刊: Automation in Construction
• 影响因子: 10.3
• 作者: Zhu, Qi;Du, Jing;Shi, Yangming;Wei, Paul
• 通讯作者: Wei, Paul

Humanlike Inverse Kinematics for Improved Spatial Awareness in Construction Robot Teleoperation: Design and Experiment

用于提高建筑机器人远程操作空间意识的类人逆运动学：设计与实验

• DOI: 10.1061/jcemd4.coeng-13350
• 发表时间: 2023-07
• 期刊: Journal of Construction Engineering and Management
• 影响因子: 5.1
• 作者: Zhou, Tianyu;Zhu, Qi;Ye, Yang;Du, Jing
• 通讯作者: Du, Jing