NRI-Large: Collaborative Research: Multilateral Manipulation by Human-Robot Collaborative Systems

NRI-Large：协作研究：人机协作系统的多边操纵

• 批准号: 1227406
• 负责人: Allison Okamura
• 金额: $ 116.34万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1227406&HistoricalAwards=false
• 关键词: NRI; Large; Collaborative; Research; Multilateral

This project addresses a large space of manipulation problems that are repetitive, injury-causing, or dangerous for humans to perform, yet are currently impossible to reliably achieve with purely autonomous robots. These problems generally require dexterity, complex perception, and complex physical interaction. Yet, many such problems can be reliably addressed with human/robot collaborative (HRC) systems, where one or more humans provide needed perception and adaptability, working with one or more robot systems that provide speed, precision, accuracy, and dexterity at an appropriate scale, combining these complementary capabilities.The project focuses on multilateral manipulation, which arises when a human controls one or more robot manipulators in partnership with one or more additional controllers (humans or autonomous agents). Complex operations in surgery and manufacturing can benefit from the extra degrees of freedom provided by more than two hands, and training often depends on hands-on interaction between expert and apprentice. Example applications include surgical operations, which typically involve several physicians and assistants, and other medical tasks such as turning a patient in bed and wrapping a cast to constrain a hand. Multilateral manipulation also applies in manufacturing, for example for threading wires or cables, aligning gaskets to obtain a tight seal, and in many household situations, such as folding tablecloths, wrapping packages, and zipping overfilled suitcases so they will fit inside diabolically-designed overhead airline compartments. Multilateral manipulation often arises with deformable materials or multi-jointed objects with more than six degrees of freedom (DOF). The extra DOFs in materials introduce challenges such as computational complexity, but they also can accommodate minor inconsistencies through redundancy and provide system damping. This project advances the fundamental science of multilateral manipulation guided by specific applications from surgery and manufacturing.Broader Impacts: Multilateral manipulation systems have the potential to improve healthcare, improve American competitiveness and product quality in manufacturing, and open the door to new service robot applications in the home. The project will be guided by an Advisory Board of experts from industry and medical practice. Project results will be disseminated through yearly conference workshops, open-source software tools integrated into common robotics software environments such as Robot Operating System (ROS), and the investigators' research and course webpages, to encourage integration of our approach into research projects and courses at many institutions. Outreach programs, public lab tours, and mentoring of minority students will broaden participation of underrepresented groups in engineering. These activities will encourage participation in STEM activities and provide student and postdoctoral researchers with mentoring experience.

该项目解决了大量重复的、造成伤害的或对人类来说危险的操作问题，但目前不可能用纯自主机器人可靠地实现。这些问题通常需要灵巧、复杂的感知和复杂的物理交互。然而，许多这样的问题可以通过人/机器人协作（HRC）系统可靠地解决，其中一个或多个人提供所需的感知和适应性，与一个或多个机器人系统一起工作，这些机器人系统以适当的规模提供速度、精度、准确度和灵活性，结合这些互补能力。这在人类与一个或多个附加控制器（人类或自主代理）合作控制一个或多个机器人操纵器时出现。手术和制造中的复杂操作可以受益于两只手以上提供的额外自由度，培训通常取决于专家和学徒之间的动手互动。示例应用包括外科手术，其通常涉及几个医生和助手，以及其他医疗任务，例如在床上翻转患者和缠绕石膏以约束手。多边操作也适用于制造业，例如穿线或电缆，对齐垫圈以获得紧密密封，以及在许多家庭情况下，例如折叠桌布，包装包装包装，以及压缩过度填充的行李箱，以便它们将适合恶魔设计的头顶航空公司隔间。多边操纵通常出现在具有六个以上自由度（DOF）的可变形材料或多关节物体中。材料中额外的自由度带来了计算复杂性等挑战，但它们也可以通过冗余来适应微小的不一致性，并提供系统阻尼。该项目通过外科手术和制造业的具体应用，推进多边操作的基础科学。更广泛的影响：多边操作系统有可能改善医疗保健，提高美国制造业的竞争力和产品质量，并为家庭中新的服务机器人应用打开大门。该项目将由来自工业和医疗实践的专家组成的咨询委员会指导。项目结果将通过年度会议研讨会、集成到常见机器人软件环境（如机器人操作系统（ROS））中的开源软件工具以及研究人员的研究和课程网页进行传播，以鼓励将我们的方法融入许多机构的研究项目和课程。外展计划，公共实验室图尔斯之旅，以及对少数民族学生的指导将扩大工程中代表性不足的群体的参与。这些活动将鼓励参与STEM活动，并为学生和博士后研究人员提供指导经验。