Achieving lifelike autonomy remains a long-term aspiration, yet soft robots so far have mostly demonstrated rudimentary physical intelligence that relies on manipulation of external stimuli to generate continuous motion. To realize autonomous physical intelligence (API) capable of self-regulated sensing, decision-making, and actuation, a promising approach is creating nonlinear time-lag feedback embedded within materials, where a constant stimulus elicits delayed responses to enable autonomous motion. This Review explores such feedback mechanisms, traces the evolution of physically intelligent robots, outlines strategies for embedding API in soft robots under diverse environments, and further discusses challenges and future directions beyond simple locomotion.

中文翻译：

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推进自主软体机器人的物理智能

实现栩栩如生的自主性仍然是一个长期的愿望，但到目前为止，软机器人大多展示了基本的物理智能，依靠纵外部刺激来产生连续的运动。为了实现能够自我调节的传感、决策和驱动的自主物理智能 （API），一种很有前途的方法是创建嵌入在材料中的非线性延时反馈，其中恒定的刺激会引起延迟响应以实现自主运动。本文探讨了此类反馈机制，追溯了物理智能机器人的演变，概述了在不同环境下将 API 嵌入软机器人的策略，并进一步讨论了超越简单运动的挑战和未来方向。