Bridging Sensing and Action: Autonomous Object Sorting by Reprogrammable Liquid Crystal Elastomers

Abstract

Achieving autonomy in soft robotics requires integrating sensing, planning, and actuation. Stimuli-responsive liquid crystal elastomers (LCEs) are promising for this purpose due to their intrinsic sensory capabilities, adaptability and integrability. Nevertheless, self-regulated LCE systems typically rely on single-mode bending actuators with feedback-type mechanisms, where deformation gradually increases with stimulus intensity but only causes a functional transition beyond a critical activation point. This enables autonomous switching between non-functional and functional states, however, their behavior remains reactive, limiting their ability to perform complex adaptive tasks. Here, we present a reprogrammable LCE actuator capable of autonomously sorting objects based on their green-light transmission properties. Using perylene diimide-doped LCEs and controlled green-light illumination, the actuator senses the optical properties of the object, establishing an actuation plan through spatial radical generation. Subsequent far-red irradiation triggers different actuation modes, enabling selective object sorting. This pattern-encoded actuation allows objects with different optical characteristics to trigger specific mechanical responses under identical illumination conditions. This single-material system, which is optically resettable, integrates sensory feedback, deliberative decision-making, and adaptive mechanical responses. Surpassing the reactive nature of conventional self-regulated LCE systems, our approach advances LCE-based robotics toward greater autonomy, aligning with the sense-plan-act paradigm.