Artificial Intelligence for Computer-Aided Detection in Biomedical Applications

人工智能在生物医学应用中的计算机辅助检测

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Abstract

Mobile robots are increasingly deployed in diverse settings, ranging from logistic and household applications to ecological monitoring and operation in extreme environments. In these contexts, robots must traverse diverse terrains, yet most existing designs rely on fixed morphologies that limit efficiency across domains. Biomimetic solutions emulate natural forms but cannot fully exploit engineered mechanisms, while active adaptive architectures typically require complex electronics and incur substantial energy costs. Inspired by amphibians and reptiles, we developed AdaptBot, an untethered adaptive soft robot that integrates rigid machinery with responsive soft materials to achieve passive reconfiguration for amphibious locomotion. AdaptBot employs a single bioinspired photothermal artificial muscle (PAM) to power multiple gaits by light, a fast and large swelling hydrogel (FLASH) to drive passive fin deployment in water, and a ratcheting transmission to convert reciprocating PAM motion into forward locomotion. These elements enable multimodal performance-including rolling, load-carrying, climbing, and paddling-under wireless control across terrestrial, aquatic, and transitional environments. Remarkably, following fin deployment, AdaptBot's swimming speed increased by 780%, demonstrating that passive adaptation is an effective strategy to enhance locomotor efficiency in robots operating in unstructured and dynamic environments.

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