This paper presents a bionic foldable wing that imitates the hind wing of ladybirds. Based on the folding mechanism of the hind wing of ladybirds and the theory of origami, the motion model of the bionic foldable wing is established, yield the motion law of the crease angles and the variation relationship between the panels are obtained. Bionic foldable wings utilise shape memory alloy to drive wings to fold, and embedded torsion springs to release energy to realize the function of wing unfolding. In the experiments of the vehicle equipped with foldable wings, the lift and attitude torque of bionic foldable wings are measured by the F/T sensor. The experimental results indicated that its aerodynamic performance is basically close to that of our optimized non-foldable wings. Moreover, the vehicle with foldable wings has been able to overcome gravity to achieve flight, which provides a novel concept for the research on flapping wing.

This paper proposes a downlink transmission scheme for intelligent reflecting surface (IRS) enhanced cognitive-satellite-aerial-network to support massive access of Internet-of-Things devices (IoTDs). By sharing the same frequency band with satellite network, the aerial network offers services for IoTDs having line-of-sight links through space division multiple access, and for IoTDs locating in blocked area via IRS-enhanced non-orthogonal multiple access. Assuming that only the imperfect channel state information is available, we formulate a transmit power minimization problem subject to the probabilistic constraints of the quality-of-service requirements for IoTDs, the co-channel interference power limitation, and unit-modulus requirement for IRS. To tackle this mathematically intractable problem, we propose a generalized zero-forcing based low-complexity robust transmission algorithm, integrating the second-order Taylor expansion and Bernstein-type inequality, to obtain a satisfactory performance while reducing the computational load. Finally, simulation results validate the effectiveness and superiority of the proposed robust algorithms compared to existing algorithms.