CAREER: Integrating Sensorimotor Models into Human-Robot Collaboration in Gait, Posture, and Unsteady Tasks

该学院早期职业发展（CAREER）资助支持研究，这将为可穿戴机器人设备的设计和控制提供新的知识，以辅助日常运动，如行走和站立平衡。可穿戴机器人设备，如外骨骼，可用于为行动不便或其他残疾的人提供辅助力量。虽然驾驶残疾的症状是不同的，具体到个人，目前的机器人还没有智能修改他们的行为，根据用户的具体需求。该奖项支持对使用者主要感官中特定缺陷的测量方法进行基础研究，以改善人类和机器人在运动任务中的协作方式。这项研究的结果将推进机器人，生物力学，神经科学和控制的跨学科知识。减少残疾的影响和帮助人们重返工作岗位将大大有利于美国推进科学和促进人类健康的经济和社会目标。这项工作的更广泛影响包括与当地高中和附近一所历史悠久的黑人大学建立培训和研究伙伴关系，以吸引和留住妇女和代表性不足的少数民族。为了估计身体的运动，人类使用三个主要的感觉系统：视觉，前庭和体感。大脑控制运动能力的一个主要因素是使用来自多个感觉系统的信息来提高估计自我运动和感觉反馈的能力。当其中一个感觉系统经历了动态的准确性损失时，例如一步过渡到柔软的地面或视力丧失，大脑通过减少受影响的感觉对整体估计的贡献来进行补偿，这一过程称为感觉重新加权。这种机器人辅助步态和姿势的基础研究将通过研究机器如何影响在存在感觉缺陷的情况下对自我运动，认知和运动控制的感知动态来推进科学理解。在第一个目标中，研究人员将使用外骨骼和虚拟现实进行实验，以确定外骨骼如何影响自主步行和站立平衡中的感觉重新加权过程。这些结果将为人机协作的物理和感官动态提供新的测量方法。在第二个目标中，他们将开发方法，将感官重新加权的个性化感知模型纳入步行和站立的模拟中。在最终目标中，他们将探索实时检测感官重加权的方法，以及使用触觉反馈作为人与机器之间交流状态和信任的工具。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development (CAREER) grant supports research that will contribute new knowledge to the design and control of wearable robotic devices for assisting everyday movements, such as walking and standing balance. Wearable robotic devices, such as exoskeletons, can be used to provide assistive forces to those who have impaired mobility or other disabilities. Although the symptoms driving disability are varied and specific to the individual, current robots do not yet have the intelligence to modify their behavior based on the user’s specific needs. This award supports fundamental research on methods to use measurements of specific deficits in the user’s primary senses to improve how humans and robots collaborate during movement tasks. The results of this research will advance interdisciplinary knowledge in robotics, biomechanics, neuroscience, and control. Reducing the impact of disability and helping people return to work will greatly benefit the U.S. economic and societal goals to advance science and promote human health. The broader impacts of this work include training and research partnerships with local high schools and a nearby historically black university to attract and retain women and underrepresented minorities. To estimate the body’s movement, humans use three primary sensory systems: visual, vestibular, and somatosensory. A major element of the brain’s ability to control movement is to use information from multiple sensory systems to improve the ability to estimate self-motion and sensory feedback. When one of the sensory systems experiences a dynamic loss of accuracy, such as a step transition into soft ground or a loss of vision, the brain compensates by reducing the contribution of the impacted sense to the overall estimation in a process called sensory reweighting. This fundamental research in robot-assisted gait and posture will advance scientific understanding by studying how machines affect the dynamics of the perception of self-motion, cognition, and motor control in the presence of sensory deficits. In the first objective, the researchers will perform experiments with the exoskeleton and virtual reality to identify how exoskeletons affect the sensory reweighting processes in self-paced walking and standing balance. These results will provide novel measurements of the physical and sensory dynamics of human-robot collaboration. In the second objective, they will develop methods to incorporate individualized perceptual models of sensory reweighting into simulations of walking and standing. In the final objective, they will explore methods for real-time detection of sensory reweighting and the usage of haptic feedback as a tool to communicate state and trust between person and machine.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.