Autonomous soft robotics: Revolutionizing motion with intelligence and flexibility.

The extraordinary efficiency of natural cyclic motions, from cardiac muscle actuation to insect wing kinematics and medusoid jet propulsion, embodies evolutionary perfection in autonomous locomotion. These biological models inspire soft robotics to achieve adaptive, efficient, and autonomous motion that emerges in compliant architectures through material-enabled self-regulation, eliminating external control dependencies. This review focuses on the key mechanisms that enable self-sustained motion in soft robots, categorizing current strategies into six representative types based on stimulus sources and structural features: thermal, light, photochemical, humidity, topological structure, and negative feedback loop. Corresponding motion behaviors are further classified into five typical modes: self-sustained oscillation, rolling or crawling, structure-mediated obstacle avoidance, topological spinning, and nonlinear trajectory motion. By comparing these mechanisms in terms of environmental adaptability, energy conversion and locomotion performance, a mapping framework is established to correlate motion strategies with environmental features. This framework supports the development of demand-adaptive and scenario-specific soft robotic systems. The review concludes by highlighting the major challenges to achieving robust, long-term autonomous behavior in unstructured environments and discussing possible future research directions.