电液驱动机器人肩部的自感知反馈控制
Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder
AI总结：
提出一种由自感知液压放大自愈合静电执行器驱动的仿生拮抗式机器人肩部，通过将高压驱动与低压自感知电极解耦实现无外部传感器的本体感觉反馈轨迹控制，为复杂肌肉骨骼关节排列奠定基础。
摘要：
人类肩部凭借其盂肱关节、肌腱、韧带和肌肉，能够精确高效地执行复杂任务。然而，当前的机器人肩部设计缺乏生物对应物所固有的柔顺性和紧凑性。这些设计的一个主要局限是依赖诸如旋转编码器等外部传感器，这限制了机械关节设计并给系统增加了体积。为了解决这一限制，我们提出了一种仿生拮抗式机器人肩部，具有两个自由度，由自感知液压放大自愈合静电执行器驱动。我们的人造肌肉设计将高压静电驱动与一对低压自感知电极解耦。该方法允许在任务空间中对轨迹进行本体感觉反馈控制，同时消除了对任何额外传感器的需求。我们通过将其与基于动作捕捉系统提供的位置数据的反馈控制进行比较，来评估该平台的有效性。该研究展示了基于电液执行器固有的自感知能力的闭环可控机器人机械臂。所提出的架构可以作为复杂肌肉骨骼关节排列的基础。
英文摘要：
The human shoulder, with its glenohumeral joint, tendons, ligaments, and muscles, allows for the execution of complex tasks with precision and efficiency. However, current robotic shoulder designs lack the compliance and compactness inherent in their biological counterparts. A major limitation of these designs is their reliance on external sensors like rotary encoders, which restrict mechanical joint design and introduce bulk to the system. To address this constraint, we present a bio-inspired antagonistic robotic shoulder with two degrees of freedom powered by self-sensing hydraulically amplified self-healing electrostatic actuators. Our artificial muscle design decouples the high-voltage electrostatic actuation from the pair of low-voltage self-sensing electrodes. This approach allows for proprioceptive feedback control of trajectories in the task space while eliminating the necessity for any additional sensors. We assess the platform's efficacy by comparing it to a feedback control based on position data provided by a motion capture system. The study demonstrates closed-loop controllable robotic manipulators based on an inherent self-sensing capability of electrohydraulic actuators. The proposed architecture can serve as a basis for complex musculoskeletal joint arrangements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
