The increasing demand for impact resistance in landing gears of low-altitude aircraft necessitates the development of buffer structures that combine lightweight properties with high energy absorption efficiency. Inspired by the graded multicellular structure of a locust’s hind leg tibia, this paper proposes a bio-inspired multicellular thin-walled tube structure (circular bionic cell thin-walled tube structure, CTTs). The effects of cell number, wall thickness distribution, and curvature parameters on the crashworthiness of the structure are systematically investigated. The deformation modes, specific energy absorption (SEA), peak force, and crush force efficiency (CFE) are analyzed through finite-element simulations and axial impact tests. The results indicate that the structure achieves optimal energy absorption performance with a cell number of 8, an outer wall thickness of 0.5 mm, a cell wall thickness of 1.0 mm, and a curvature ratio R/r of 1.5, yielding a SEA of 34.25 J / g and a significantly improved CFE. The bio-inspired structure exhibits stable progressive folding deformation, offering a novel design strategy for high-performance unmanned aerial vehicle landing gears.

With unique advantages in flexibility, adaptability, and safety, pneumatic artificial muscle (PAM) has been widely applied in fields such as rehabilitation medical robots and soft robotic arms. This paper develops a PAM-driven lower-limb exoskeleton robot for lower-limb motor rehabilitation. Due to inherent characteristics of PAMs, such as parameter disturbances and hysteresis effects, a magnetorheological damper (MRB) with real-time adjustable damping characteristics is introduced in this study to enhance the motion stability of the PAM-driven rehabilitation robot. Furthermore, an input-output constrained adaptive neural network control method suitable for flexible joint robots is proposed. To verify the effectiveness of the proposed control algorithm on the PAM-driven rehabilitation robot, a series of experiments were conducted on a self-built exoskeleton robot. Compared with the classical PID control, this method can track the desired trajectory faster, and the tracking accuracy gradually improves.