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.

翻译：人类的肩关节，凭借其盂肱关节、肌腱、韧带和肌肉，能够精确高效地完成复杂任务。然而，当前的机器人肩关节设计缺乏其生物对应结构的柔顺性和紧凑性。这些设计的一个主要缺点是依赖外部传感器（如旋转编码器），这限制了机械关节的设计并增加了系统体积。为解决这一限制，我们提出了一种受生物启发的、具有两个自由度的拮抗式机器人肩关节，其动力来自自感知液压放大自愈合静电致动器。我们的人工肌肉设计将高压静电致动与一对低压自感知电极解耦。这种方法可以在任务空间中实现轨迹的本体感觉反馈控制，同时消除了对任何额外传感器的需求。我们通过与基于运动捕捉系统提供的位置数据的反馈控制进行比较，评估了该平台的效能。本研究展示了基于电液致动器固有自感知能力的闭环可控机器人操作器。所提出的架构可成为复杂肌肉骨骼关节布局的基础。