Geometry-Encoded Actuation as a Structural Interaction Layer in Origami Robots

Physical interaction in robotics predominantly relies on sensing, computation, and feedback control, resulting in increasing system complexity. Here, we introduce geometry-encoded actuation (GEA), a design framework that exploits multistable origami geometries as programmable physical interaction layers to mechanically encode environmental stimuli into autonomous structural responses. By integrating multistable origami with liquid crystal elastomer (LCE) actuators, GEA couples structural geometry, energy landscapes, and stimuli-responsive actuation to achieve programmable shape transformation without continuous sensing or complex control during the interaction process. A theoretical framework based on spherical geometry, energy analysis, and structural optimization is established to guide the design of bistable origami mechanisms. The proposed framework is validated through representative robotic systems, including a bistable origami gripper, an adaptive origami wheel, and autonomous locomotion and manipulation demonstrations, achieving up to 45% actuation strain, 106 ${}^{\circ }$ programmable geometric transformation, 100% task success in 10 consecutive trials, and stable operation after 500 actuation cycles. By embedding interaction intelligence directly into structural geometry, GEA redistributes part of the interaction complexity from computation to morphology, providing a general framework for programmable physical intelligence and adaptive embodied robotic systems.