🤖 AI Summary
Conventional untethered amphibious soft robots suffer from limited locomotion modalities and reliance on external actuation or control systems, hindering autonomous operation in multi-task environments.
Method: Inspired by inchworms, we propose a co-design methodology integrating magnetically actuated flexible structures with system-level hardware integration. A magnetically bent compliant body enables dual-mode locomotion—crawling on land and swimming in water—while embedded wireless control electronics and an onboard camera support full autonomy, real-time environmental perception, and closed-loop motion regulation.
Contribution/Results: The resulting robot weighs 102.63 g and achieves maximum speeds of 3.74 cm/s (crawling) and 0.82 cm/s (swimming). It successfully performs complex tasks including steering, obstacle traversal, aquatic propulsion, and payload transport. To our knowledge, this is the first lightweight, fully autonomous, wirelessly controlled amphibious soft robot, eliminating constraints imposed by tethers or external drivers. The work establishes a scalable design paradigm for multi-domain adaptive soft robotics.
📝 Abstract
Untethered soft robots are essential for advancing the real-world deployment of soft robotic systems in diverse and multitasking environments. Inspired by soft-bodied inchworm, we present a fully untethered soft robot with a curved, flexible structure actuated by magnetic forces. The robot has a total mass of 102.63 g and demonstrates multimodal locomotion, achieving a maximum walking speed of 3.74 cm/s and a swimming speed of 0.82 cm/s. A compact and lightweight onboard control circuit enables wireless command transmission, while an integrated camera provides environmental perception. Through structural optimization and system-level integration, the robot successfully performs walking, steering, swimming, and payload transport without reliance on external infrastructure. The robot's dynamic performance and locomotion capabilities are systematically validated through experimental characterization.