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Assist-as-needed Impedance Control Strategy for a Wearable Ankle Robotic Orthosis

机译:可穿戴踝部机器人矫形器的辅助防止控制策略

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The use of robots in rehabilitation attempts an effective, compliant, and time-efficient gait recovery while adapting the assistance to the user’s needs. Assist-as-needed strategies (AAN), such as adaptive impedance control, have been reported as prominent strategies to enable this recovery effects. This study proposes an interaction-based assist-as-needed impedance control strategy for an ankle robotic orthosis that adapts the robotic assistance by changing the Human-Robot interaction stiffness. The adaptability of the interaction stiffness allows the real-time passage from passive assistance to an active one, approaching AAN gait training. The interaction stiffness was successfully estimated by linear regression of the Human-Robot interaction torque vs angle trajectory curve. From the validation with seven able-bodied subjects, we verified the suitability of this adaptive impedance control for a more compliant, natural, and comfortable motion than the trajectory tracking control. Moreover, the proposed strategy considers the users’ motion intention and encourages them to interact closely with the robotic device while guiding their ankle trajectory according to desired trajectories. These achievements contribute to AAN gait training.
机译:在康复中使用机器人试图有效,兼容,节约效率的步态恢复,同时调整对用户需求的援助。诸如自适应阻抗控制的辅助策略(AAN)被报告为启用这种恢复效果的突出策略。本研究提出了一种基于互动的辅助阻抗控制策略,用于踝关节机器人矫形器,通过改变人机互动刚度来适应机器人辅助。相互作用刚度的适应性允许从被动辅助到有效的实时通道,接近AAN步态训练。通过人机组织交互扭矩与角度轨迹曲线的线性回归成功地估计了相互作用刚度。从七个能够拥有七个能够的验证,我们验证了这种自适应阻抗控制的适用性,以便比轨迹跟踪控制更符合更符合的,自然,舒适的运动。此外,该拟议的策略考虑了用户的运动意图,并鼓励他们根据所需的轨迹引导其脚踝轨迹密切地与机器人设备进行互动。这些成就有助于AAN步态培训。

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