Numerous diseases and aging can cause degeneration of people's balance ability resulting in limited mobility and even high risks of fall. Robotic technologies can provide more intensive rehabilitation exercises or be used as assistive devices to compensate for balance ability. However, With the new healthcare paradigm shifting from hospital care to home care, there is a gap in robotic systems that can provide care at home. This paper introduces Mobile Robotic Balance Assistant (MRBA), a compact and cost-effective balance assistive robot that can provide both rehabilitation training and activities of daily living (ADLs) assistance at home. A three degrees of freedom (3-DoF) robotic arm was designed to mimic the therapist arm function to provide balance assistance to the user. To minimize the interference to users' natural pelvis movements and gait patterns, the robot must have a Human-Robot Interface(HRI) that can detect user intention accurately and follow the user's movement smoothly and timely. Thus, a graceful user following control rule was proposed. The overall control architecture consists of two parts: an observer for human inputs estimation and an LQR-based controller with disturbance rejection. The proposed controller is validated in high-fidelity simulation with actual human trajectories, and the results successfully show the effectiveness of the method in different walking modes.
翻译:多种疾病和衰老会导致人们的平衡能力退化,从而导致行动能力受限,甚至高风险摔倒。机器人技术可以提供更密集的康复训练,或用作辅助设备来弥补平衡能力的不足。然而,随着新的医疗保健范式从医院护理转向家庭护理,存在一个在家提供护理的机器人系统空缺。本文介绍了移动式机器人平衡辅助器(Mobile Robotic Balance Assistant, MRBA),这是一种紧凑、成本效益高的平衡辅助机器人,可以在家中提供康复训练和日常生活(ADLs)援助。设计了一个三自由度(3-DoF)的机械臂来模仿治疗师的手臂功能,为用户提供平衡辅助。为了最小化对用户自然骨盘运动和步态模式的干扰,机器人必须具有能够准确检测用户意图并平滑及时地跟随用户运动的人机界面(HRI),因此,提出了优雅的用户跟随控制规则。总体控制架构由两部分组成:用于人类输入估计的观察器和带干扰抵消的基于LQR的控制器。将所提出的控制器在具有实际人类轨迹的高保真模拟中进行验证,结果成功地展示了该方法在不同步态中的有效性。