Extended reality (XR) work-cell for safe human-centered robotics research
Extended reality (XR) work-cell for safe human-centered robotics research
批准号:
RTI-2023-00418
负责人:
Najjaran, Homayoun
金额:
$5.06万
依托单位:
依托单位国家:
加拿大
项目类别:
Research Tools and Instruments
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
以人为中心的机器人技术是所有机器人技术在现实世界中安全运行不可或缺的一个方面,因此已经成为机器人界和自动化行业中最有影响力的研究课题之一。该项目旨在为以人为中心的自主机器人研究创建一个以安全为重点的设计、开发和评估工作单元。它将使人-机器人协作(HRC)、有效的多模式人机交流和协作机器人(co-bot)的模拟和实验研究成为可能。机器人和人类在共享工作单元中的协同作用为许多行业面临的挑战提供了令人信服的解决方案,包括敏捷制造和高度可定制的生产。在典型的HRC场景中,机器人旨在执行危险的、非人体工学的和重复的任务,而人类合作伙伴专注于认知决策和非传统任务,从而提高吞吐量和质量。人类和机器人协同工作的异质设置需要所有代理之间的实时通信。从实践的角度来看,一个重要的研究问题是,人类和机器人之间的不同通信方式是什么组合,以及在多大程度上,才能在嘈杂、拥挤和高度动态的环境中提供安全和连续的操作。这意味着,具有HRC自然流畅性和无缝团队活力的有效多模式通信的发现,将导致自动化和制造业等广泛行业的巨大范式转变。所提出的研究的目的是调查有希望的通信手段(例如,视觉、手势和肢体语言)和协议(即,真实和虚拟),用于协调通过多个输入通道(模式)实现的任务,这些输入通道(模式)对于工业环境中的人类操作员来说是自然的。机器人工作组还将加强目前在制造、社会和工业机器人以及自动驾驶汽车领域的行业合作,同时在现有合作伙伴关系之外培养新的合作伙伴关系。申请者和他的共同申请者需要设备来带头他们以人类为中心的机器人研究计划。进入机器人工作单元将加快这一时间敏感领域的研究进展,帮助学生在论文和出版物中传播可验证的结果,提高所开发原型的技术准备,并促进工业自动化和网络物理系统的创新。为此,拟议的工作小组将为来自不同性别、背景、学术准备和纪律的50多名研究生和博士后,以及能够远程连接到工作小组并通过其模拟、数据生成和虚拟现实能力从设置中受益的外部用户提供一个免费访问和公平的HQP培训平台。
英文摘要
Human-centered robotics has emerged as one the most influential research topics in the robotics community and automation industry for it is an integral aspect of safe functioning of all robotic technologies in real-world scenarios. This project aims to create a design, development and evaluation work-cell for human-centered autonomous robot research with emphasis on safety. It will enable simulated and experimental research on human-robot collaboration (HRC), effective multi-modal human-machine communication and collaborative robots (co-bots). Synergy between robots and humans in a shared work-cell provides a compelling solution to the challenges faced by many industries including agile manufacturing and highly customizable production. In a typical HRC scenario, robots are meant to carry out dangerous, non-ergonomic and repetitive tasks while the human partners concentrate on cognitive decision making and nonconventional tasks leading to improved throughput and quality. A heterogenous setup of humans and robots working collaboratively requires real-time communication between all agents. From a practical standpoint, an important research question is what combination of, and to what extent, different communication means among human and robot agents can provide a safe and continuous operation in the noisy, crowded and highly dynamic environments. This means that the discovery of effective multi-modal communications with the natural fluency and seamless team dynamics of HRC will lead to a dramatic paradigm shift in broad industries such as automation and manufacturing. The aim of the proposed research is to investigate promising communication means (e.g., visual, gestural and body language) and protocols (i.e., both real and virtual) for coordination of tasks achieved through multiple input channels (modes) that are natural to human operators in industrial settings. The robot work-cell will also strengthen current industry collaborations in the areas of manufacturing, social and industrial robotics, and autonomous vehicles, while fostering new partnerships beyond the existing ones. The applicant and his co-applicants need the equipment to spearhead their human-centered robotics research initiative. Access to the robot work-cell will accelerate research progress in this time-sensitive area, help students disseminate verifiable results in their theses and publications, improve the technology readiness of the prototypes developed, and facilitate innovations in industrial automation and cyber-physical systems. To that end, the proposed work-cell will provide a free-access and equitable HQP training platform for not only over 50 graduate students and postdocs from a diverse group in terms of gender, background, and academic preparedness and discipline but also external users who can connect to the work-cell remotely and benefit from the setup through its simulation, data generation, and virtual reality capabilities.
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