光学传感电织带执行器（OS-ERA）
Optically Sensorized Electro-Ribbon Actuator (OS-ERA)
AI总结：
OS-ERA通过光学传感实现高精度弯曲状态分类，解决ERAs的传感精度瓶颈，实现快速且可重复的闭环控制
摘要：
电织带执行器（ERAs）是一种轻量的弯曲执行器，能够实现超大的位移和快速运动。然而，其内置的传感依赖于电容传感器，精度有限，这阻碍了精确控制。我们引入了OS-ERA，一种光学传感的ERAs，能够提供可靠的本体感觉信息，并专注于传感解决方案的设计和集成，而不影响执行。为了分析ERAs在运动中的复杂曲率，我们设计并嵌入了两个柔软的光学波导传感器。一个分类器被训练以将传感信号映射到八个弯曲状态。我们在六个保留试验中验证了我们的模型，并将其与从训练运行中学习的信号轨迹进行比较。在所有测试中，传感输出信号遵循训练流形，预测序列与实际性能一致并确认了可重复性。尽管在执行速度上故意存在训练-测试不匹配，信号轨迹仍然保持其形状，分类仍然保持一致的准确性，证明了实际电压和速度不变性。因此，OS-ERA能够高保真地分类弯曲状态；它快速且可重复，解决了ERAs长期存在的瓶颈，朝着闭环控制迈进。
英文摘要：
Electro-Ribbon Actuators (ERAs) are lightweight flexural actuators that exhibit ultrahigh displacement and fast movement. However, their embedded sensing relies on capacitive sensors with limited precision, which hinders accurate control. We introduce OS-ERA, an optically sensorized ERA that yields reliable proprioceptive information, and we focus on the design and integration of a sensing solution without affecting actuation. To analyse the complex curvature of an ERA in motion, we design and embed two soft optical waveguide sensors. A classifier is trained to map the sensing signals in order to distinguish eight bending states. We validate our model on six held-out trials and compare it against signals' trajectories learned from training runs. Across all tests, the sensing output signals follow the training manifold, and the predicted sequence mirrors real performance and confirms repeatability. Despite deliberate train-test mismatches in actuation speed, the signal trajectories preserve their shape, and classification remains consistently accurate, demonstrating practical voltage- and speed-invariance. As a result, OS-ERA classifies bending states with high fidelity; it is fast and repeatable, solving a longstanding bottleneck of the ERA, enabling steps toward closed-loop control.
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。
