AmphiHip Exo: A Cable-Driven Amphibious Hip Exoskeleton With Physics-Informed Intention Perception for Lower Limb Augmentation

Developing an amphibious hip powered exoskeleton (AHPE) for lower limb augment in amphibious environments is crucial, which is facing the challenges, such as mechanical design, effective human-exoskeleton interaction, and simulating scenarios, for performance validations. To tackle these issues, this work proposes a design of a cable-driven AHPE named AmphiHip Exo for the hip flexion/extension assisting. To achieve an effective human-exoskeleton interaction, a physics-informed neural network named PILaN is proposed to realize hip motion intention perception (HMIP)-based control of the AmphiHip Exo. Trained by a self-collected small-scale dataset containing hip states of human activities, the proposed PILaN can automatically proceed HMIP, including joint trajectory and velocity estimations, with real-time dynamics parameter estimations and the Lagrangian dynamics model. Prototype tests are conducted on various wearers under four designed task scenarios: daily handling, climbing stairs, underwater gait assistance, and water rescue, and the performances are validated according to our designed evaluation metrics: HMIP accuracy, power assisting effect (PAE), and mechanical reliability. Experimental results prove the accuracy and efficiency of PILaN, the PAE among different wearers and task scenarios, and the waterproof effect as well as battery endurance, demonstrating the feasibility of the designed AmphiHip Exo.