Artificial muscle fibers have attracted widespread attention and demonstrated great potential for applications in smart robots, wearable electronics, biomedicine, etc. In particular, lightweight, flexible, and compact perception-actuation integrated artificial muscle fibers have become a hot research topic since they are expected to be widely used in some complex intelligent structures and systems to replace traditional mechanical sensing and actuating units, thereby enabling weight reduction of the entire device. Mimicking the mammalian neuromuscular system, the functionally integrated artificial muscle fibers can accurately perceive changes in the external environment and actuate accordingly. However, owing to the limitations of materials, structures, and control systems, the comprehensive performance of perception-actuation integrated artificial muscle fibers is far inferior to that of the natural neuromuscular system. Specifically, interface problems and lack of advanced synergy between sensing and actuating units result in hysteresis in perception and self-sensing signals. Therefore, it is highly necessary to summarize the research field of perception-actuation integrated artificial muscle fibers and gain insights into the impact of structural design on perception and actuation performance to guide their rapid development in the future.

中文翻译：

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感知-驱动集成人造肌肉纤维：从结构设计到应用

人造肌肉纤维受到广泛关注，在智能机器人、可穿戴电子、生物医学等领域展现出巨大的应用潜力，特别是轻质、灵活、紧凑的感知-驱动一体化人造肌肉纤维已成为研究热点，因为它有望成为研究的热点。可广泛应用于一些复杂的智能结构和系统中，替代传统的机械传感和执行单元，从而实现整个设备的减重。模仿哺乳动物的神经肌肉系统，功能集成的人造肌肉纤维可以准确感知外部环境的变化并做出相应的动作。然而，由于材料、结构和控制系统的限制，感知-驱动一体化人工肌肉纤维的综合性能远不如天然神经肌肉系统。具体来说，接口问题以及传感和执行单元之间缺乏先进的协同作用会导致感知和自传感信号的滞后。因此，非常有必要对感知-驱动一体化人工肌纤维的研究领域进行总结，深入了解结构设计对感知和驱动性能的影响，以指导其未来的快速发展。