ABSTRACT

Utilizing exoskeleton devices to help elderly or empower workers is a growing field of research in robotics. The structure of an exoskeleton can vary depending on user’s physical dimensions, joints or muscles targeted for assistance, and maximum achievable actuator torque. In this research, a Human-Model-In-the-Loop (HMIL) constrained optimization technique is proposed to design the RoboWalk lower-limb exoskeleton. RoboWalk is an under-actuated non-anthropomorphic assistive robot, that besides applying the desired assistive force, exerts an undesirable disturbing force leading to the user’s fall. The HMIL method uses the augmented human-robot 2D model to take RoboWalk and human body’s joint torques into account during optimization. The superiority of HMIL method is proven by comparing the results with other strategies in the literature. Obtained results reveal elimination of the disturbing forces, 2 N.m. reduction in average human knee-joint torque, and significant decrease in the actuator required torque.

摘要

利用外骨骼设备帮助老年人或赋予工人权力是机器人研究的一个不断发展的领域。外骨骼的结构可能会因用户的身体尺寸、目标关节或肌肉以及可实现的最大致动器扭矩而异。在这项研究中，提出了一种人体模型在环 (HMIL) 约束优化技术来设计 RoboWalk 下肢外骨骼。RoboWalk 是一种欠驱动的非拟人辅助机器人，它除了施加所需的辅助力外，还会施加不良的干扰力，导致用户跌倒。HMIL 方法使用增强的人机 2D 模型在优化过程中考虑 RoboWalk 和人体的关节扭矩。通过将结果与文献中的其他策略进行比较，证明了 HMIL 方法的优越性。