机器人通过内外刺激自我调节，实现持续适应性行为。
Reflexive Input-Output Causality Mechanisms
- 借鉴生物反射机制，让机器人根据内外刺激自动调整形态或动作。
- 通过反馈循环使变化自身成为新输入，实现连续自适应。
- 适合研究自适应机器人、具身智能及生物启发系统的人参考。
本文探讨了反射式驱动的概念，研究机器人如何利用内部和外部刺激触发其运动、性能或物理特性（如尺寸、形状或配置）的变化，而这些变化又可作为后续适应的输入，形成反馈循环。受生物系统中反射机制的启发，这种反射式驱动对机器人应对多样化环境、执行复杂任务至关重要。文中分析了其基本原理，并提供了接触敏感反射臂、物理计数器等现有实现案例及其应用。同时，论文展望了该领域的未来方向与挑战，强调其在发展自适应、响应式机器人系统中的重要意义。
原文摘要 · Abstract (English)
This paper explores the concept of reflexive actuation, examining how robots may leverage both internal and external stimuli to trigger changes in the motion, performance, or physical characteristics of the robot, such as its size, shape, or configuration, and so on. These changes themselves may in turn be sequentially re-used as input to drive further adaptations. Drawing inspiration from biological systems, where reflexes are an essential component of the response to environmental changes, reflexive actuation is critical to enable robots to adapt to diverse situations and perform complex tasks. The underlying principles of reflexive actuation are analyzed, with examples provided from existing implementations such as contact-sensitive reflexive arms, physical counters, and their applications. The paper also outlines future directions and challenges for advancing this research area, emphasizing its significance in the development of adaptive, responsive robotic systems.
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