Fundamentals for Motor Control of Robotic Augmentation

机器人增强运动控制基础知识

• 批准号: EP/X040372/1
• 负责人: Tamar Makin
• 金额: $ 219.58万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX040372%2F1
• 关键词: Fundamentals; Motor; Control; Robotic; Augmentation

AUGMENT is centred around the unique challenge of controlling motor augmentation technology. We are witnessing the rise of a novel class of technologies, designed to resemble human limbs in their functionalities. These extra fingers and arms are robotic devices that are designed to extend the user's motor capabilities (hereafter X-devices). Beyond the traditional substitution of missing functions, X-devices can be further exploited to provide additional motor functions to already fully functional individuals. But what cognitive and physiological resources could we utilise to control extra limbs, in addition to our own? The goal of AUGMENT is to harness basic understanding of human motor learning and control to guide successful technological development of X-devices in abled and disabled individuals. An urgent question is how to provide motor commands and somatosensory feedback to and from the X-device without restricting the cognitive and motor control of the biological limbs. I will address this by first identifying the neurocognitive mechanisms best suited for successful X-devices motor control. Then I will investigate the optimal integration of somatosensory information from the X-device to afford intuitive and transferable motor skill learning. Finally, I will provide innovative solutions for increasing the functionality of disabled individuals in daily life, beyond traditional substitution, using novel X-devices. By identifying and solving the fundamental sensorimotor human-device interface challenges across diverse user groups and functional needs, AUGMENT will be crucial for the realisation of motor augmentation and other related technologies that aim to put the user at the centre of robot control, design and development.

AUGMENT围绕着控制电机增强技术的独特挑战。我们正在见证一类新型技术的兴起，这些技术的设计在功能上类似于人类的四肢。这些额外的手指和手臂是机器人设备，旨在扩展用户的运动能力（以下简称x设备）。除了传统的替代缺失功能之外，X-devices还可以进一步开发，为已经功能齐全的个人提供额外的运动功能。但是，除了我们自己的肢体之外，我们还可以利用哪些认知和生理资源来控制额外的肢体呢？AUGMENT的目标是利用对人类运动学习和控制的基本理解来指导残疾人x设备的成功技术开发。一个迫切的问题是，如何在不限制生物肢体的认知和运动控制的情况下，向x设备提供运动命令和体感反馈。我将通过首先确定最适合于成功的x设备运动控制的神经认知机制来解决这个问题。然后，我将研究来自x设备的体感信息的最佳整合，以提供直观和可转移的运动技能学习。最后，我将提供创新的解决方案，以增加残疾人在日常生活中的功能，超越传统的替代，使用新颖的x设备。通过识别和解决跨越不同用户群体和功能需求的基本感觉运动人机界面挑战，AUGMENT将对实现运动增强和其他相关技术至关重要，这些技术旨在将用户置于机器人控制、设计和开发的中心。