Using kinesthetic feedback to improve human-robotic control

利用动觉反馈改善人机控制

• 批准号: RGPIN-2019-05961
• 负责人: Hebert, Jacqueline
• 金额: $ 2.4万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738622
• 关键词: Using; kinesthetic; feedback; improve; human

A seamless integration of sensation and motor function allows humans to effortlessly move their limbs to interact with the environment. Crucial to control of a human arm is continuous sensory feedback encompassing vision, proprioception (the sense of where the limbs are in space) and kinesthesia (movement sense), which are rapidly integrated into motor execution. This communication is disrupted when there is a machine in the loop, as is required for advanced robotic control. Integrating relevant sensory feedback from a robotic machine into natural sensory-motor human processes should improve the controllability of these devices. The kinesthetic illusion (KI) is one method for eliciting movement sensation, which is critical to successful endpoint control of a real (or possibly a robotic) limb. The KI is a perceptual illusion whereby vibrating the muscle tendons creates the feeling as though the limb is moving, although it is stationary. My research will investigate whether the KI can be integrated into a human's control of a robotic system to enhance the accuracy of positioning and grasping tasks. In my first research theme, I will define practical approaches to reliably produce movement sensations in healthy adults by manipulating experimental factors such as vibration, skin stretch, muscle contraction, and visual input. This work will provide essential knowledge on how to optimize the experience of the kinesthetic illusion. My second research theme will explore how kinesthetic sensations can be integrated into functional control of a robotic system. I will investigate the ability to use the KI to enhance robotic control accuracy for positioning and gripping tasks. This work will inform my long-term research objective which is to implement new technical approaches to non-invasively interface with humans to consistently communicate the state of an external robotic device with complex joint movements. This information will provide new knowledge for the research community on manipulating the experience of the KI through external experimental factors, and result in the development of new techniques that will have relevance for ongoing research on the use of naturally integrated feedback for human-robotic control applications. By harnessing existing knowledge of the neurophysiology of sensory-motor integration, my research will provide a sound basis for practical translation of these techniques to provide effective feedback from robotic machines to human users.

感觉和运动功能的无缝结合使人类可以毫不费力地移动肢体与环境互动。对人类手臂的控制至关重要的是持续的感觉反馈，包括视觉、本体感觉(肢体在空间中的位置感觉)和运动感觉(运动感觉)，它们迅速整合到运动执行中。当回路中有一台机器时，这种通信就会中断，这是高级机器人控制所需的。将来自机器人的相关感觉反馈整合到自然的感觉-运动人类过程中，应该会改善这些设备的可控性。动觉错觉(KI)是一种诱导运动感觉的方法，这对成功控制真实(或可能是机器人)肢体的终点至关重要。KI是一种知觉错觉，通过振动肌腱产生一种感觉，就像肢体在移动一样，尽管它是静止的。我的研究将调查KI是否可以集成到人类对机器人系统的控制中，以提高定位和抓取任务的准确性。在我的第一个研究主题中，我将定义实用的方法，通过操纵振动、皮肤拉伸、肌肉收缩和视觉输入等实验因素，在健康的成年人中可靠地产生运动感觉。这项工作将为如何优化动觉错觉的体验提供必要的知识。我的第二个研究主题将探索如何将动觉感觉整合到机器人系统的功能控制中。我将研究使用KI来提高定位和抓取任务的机器人控制精度的能力。这项工作将成为我的长期研究目标，即实现与人类非侵入性接口的新技术方法，以一致地传达具有复杂关节运动的外部机器人设备的状态。这些信息将为研究界提供关于通过外部实验因素操纵KI经验的新知识，并导致新技术的开发，这些新技术将与正在进行的使用自然集成反馈用于人-机器人控制应用的研究相关。通过利用感觉-运动整合的神经生理学的现有知识，我的研究将为这些技术的实际翻译提供可靠的基础，以便从机器人机器向人类用户提供有效的反馈。