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：多种疾病和老龄化可能导致人们平衡能力退化，造成行动受限甚至跌倒风险增高。机器人技术可提供更密集的康复训练，或用作辅助设备以弥补平衡能力不足。然而，随着医疗模式从医院护理向家庭护理转变，在居家护理机器人系统方面仍存在空白。本文提出移动式平衡辅助机器人（MRBA），这是一种紧凑且成本效益高的平衡辅助机器人，可在家庭环境中同时提供康复训练和日常生活活动辅助。设计了一个三自由度机械臂来模拟治疗师的手臂功能，为用户提供平衡辅助。为了最小化对用户自然骨盆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、及时跟随用户运动的人机交互界面。为此，提出了一种优雅的用户跟随控制律。整体控制架构由两部分组成：用于估计人体输入的观测器和基于线性二次型调节器（LQR）的扰动抑制控制器。通过高保真仿真结合真实人体轨迹验证了所提控制器的有效性，结果成功展示了该方法在不同行走模式下的性能。