NRI: Biologically Inspired Feedback Control of Robots Interacting with Humans to Cooperate and Assist with Repetitive Movement Tasks

NRI：与人类交互的机器人的仿生反馈控制，以合作和协助重复性运动任务

• 批准号: 1427313
• 负责人: Tetsuya Iwasaki
• 金额: $ 45万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1427313&HistoricalAwards=false
• 关键词: NRI; Biologically; Inspired; Feedback; Control

Biologically inspired feedback control of robots interacting with humans to cooperate and assist with repetitive movement tasksThe project will address the fundamental problem of how to control the motion of a robot so that it can cooperatively work with humans to assist them in repetitive tasks. Oscillatory body movements constitute an elementary means for various tasks in human living. Such repetitive movements include essential life functions such as heart beat, breathing, eating (chewing), walking; basic daily tasks such as brushing teeth, washing face; house-hold chores such as cleaning windows, sweeping floor; health/entertainment activities such as dancing, swimming, cycling, rowing; and manufacturing labors such as moving objects in factory assembly lines. Robots and mechanical devices that assist such human movements would be found useful in a number of contexts. A robotic manipulator and a human arm may grab a common tool to work together on repetitive tasks where the former assists the latter by providing force and stability to reduce burden on the human. An exoskeleton may be worn to complement reduced capability of, or provide rehabilitations for, elderly people and patients with neurological disorders or physical disabilities. Thus, well-designed assistive devices for oscillatory movements would significantly contribute to improving quality of human life. Design of robotic mechanisms for such assistive devices is surely a challenging task. Equally challenging is the design of control algorithms that command the actuators and govern the motion of the robotic device. The state-of-the-art control technologies allow a designer to program a robot to achieve prescribed motion with speed, precision, and robustness, as seen for instance in industrial manipulators. However, if such robots interact with humans, they would be perceived as stiff, stubborn, or even dangerous, and are therefore not suitable as co-robots in direct support of humans. What is needed is control algorithms that make robots understand human intentions, cooperate with humans without insisting on their preprogramed operations, and assist with human tasks. Development of such algorithms will be the focus of this project.This basic research aims to establish a systematic method for designing a feedback controller for a general robotic system interacting with a human to stabilize the oscillation intended by the human and to reduce the burden on the human by providing assistive forces. The control architecture is inspired by the central pattern generator (CPG) -- neuronal circuits that command muscle contractions to achieve rhythmic body movements during animal locomotion. CPGs are attractive for engineering applications due to its ability to conform their oscillations to natural dynamics of a varying environment through sensory feedback. This exploratory research will investigate the potential of the CPG architecture to provide a viable foundation for a new system design for achieving co-robots that assist humans to execute oscillation tasks. The controller is realized as an interconnection of identical units, emulating neuronal dynamics. The problem is formulated as the search for the interconnection such that the robot-human-CPG system has a stable limit cycle in which human decides an appropriate oscillation and CPG-controlled robot assists. The method of multivariable harmonic balance will be employed to obtain a convex characterization of feasible interconnection matrices that meet oscillation specifications. The approximate nature of the design method will be complemented by extensive simulations as well as physical experiments on robotic manipulators. While the central theme of control theory has been the regulation around an equilibrium point of a dynamical system, capability of generating coordinated autonomous oscillations can be extremely useful in many engineering applications. The basic research proposed here will provide an initial stepping stone toward a new paradigm for cooperative pattern generations by feedback control.

受生物启发的机器人与人类互动的反馈控制，以合作和协助重复的运动任务该项目将解决如何控制机器人的运动，使其能够与人类合作，帮助他们完成重复的任务这一根本问题。摆动的身体运动构成了人类生活中各种任务的基本手段。这种重复的运动包括基本的生活功能，如心跳、呼吸、进食(咀嚼)、走路；基本的日常任务，如刷牙、洗脸；家务劳动，如擦窗户、扫地；健康/娱乐活动，如跳舞、游泳、骑自行车、划船；以及制造劳动力，如在工厂流水线上移动物体。协助这种人类运动的机器人和机械设备将在许多情况下被发现是有用的。机器人机械手和人类手臂可以抓住一个共同的工具一起工作在重复的任务中，前者通过提供力量和稳定性来帮助后者减轻人类的负担。可以佩戴外骨骼来补充老年人和患有神经障碍或身体残疾的患者的能力下降，或为他们提供康复。因此，设计良好的摆动辅助装置将极大地提高人类的生活质量。为这类辅助设备设计机器人机构肯定是一项具有挑战性的任务。同样具有挑战性的是控制算法的设计，这些算法控制执行器并控制机器人设备的运动。最先进的控制技术允许设计师对机器人进行编程，以实现指定的运动速度、精度和健壮性，例如在工业机械手中就可以看到。然而，如果这样的机器人与人类互动，它们将被视为僵硬、顽固甚至危险，因此不适合作为直接支持人类的合作机器人。需要的是控制算法，使机器人理解人类的意图，在不坚持预先编程的操作的情况下与人类合作，并协助人类完成任务。这项基础性研究旨在建立一种系统的方法来设计一般机器人系统的反馈控制器，以稳定人类预期的振荡，并通过提供辅助力来减轻人类的负担。控制结构的灵感来自于中央模式发生器(CPG)--在动物运动过程中，指挥肌肉收缩以实现有节奏的身体运动的神经电路。CPGS由于能够通过感官反馈使其振动与变化环境的自然动力学相一致，因此在工程应用中具有吸引力。这项探索性研究将探索CPG架构的潜力，为实现辅助人类执行振荡任务的协作机器人的新系统设计提供可行的基础。该控制器被实现为相同单元的互连，模拟神经元动力学。该问题被描述为寻找互联，使得机器人-人-CPG系统存在一个稳定的极限环，在该极限环中，人类决定适当的振荡，CPG控制的机器人辅助。利用多变量调和平衡法得到满足振荡指标的可行互联矩阵的凸性刻画。设计方法的近似性将得到广泛的模拟以及对机器人操作器的物理实验的补充。虽然控制理论的中心主题是围绕动力系统的平衡点进行调节，但产生协调自主振荡的能力在许多工程应用中可能非常有用。本文提出的基础研究将为通过反馈控制合作模式生成的新范式提供初步的垫脚石。