Flying vertebrates exhibit sophisticated wingbeat kinematics. Their specialized forelimbs allow for the wing morphing motion to couple with the flapping motion during their level flight. Previous flyable bionic platforms have successfully applied bioinspired wing morphing but cannot yet be propelled by the morphing-coupled wingbeat pattern. Spurred by this, we develop a bioinspired flapping-wing aerial vehicle entitled RoboFalcon, which is equipped with a novel mechanism to drive the bat-style morphing wings, performs a morphing-coupled wingbeat pattern, and overall manages an appealing flight. The novel mechanism of RoboFalcon allows coupling the morphing and flapping during level flight and decoupling these when maneuvering is required, producing a bilateral asymmetric downstroke affording high rolling agility. The bat-style morphing wing is designed with a tilted mounting angle around the radius at the wrist joint to mimic the wrist supination and pronation effect of flying vertebrates’ forelimbs. Wind tunnel tests indicate that the rolling moment of the asymmetric downstroke is correlated with the flapping frequency, and the wrist mounting angle can be used for tuning the angle of attack, lift-thrust configuration, and power consumption of the equilibrium flight state. The agility of RoboFalcon is assessed through several tethered rolling maneuvers and outdoor free flight tests, and we present a concise analysis of the vehicle's lateral dynamics model based on system identification. We believe that this article yields a well-performing bionic platform and provides a new actuation strategy for the morphing-coupled flapping flight.

Unmanned Aerial Vehicles (UAVs) have become critical enablers of integrated air-space-ground Internet of Things (IoT) ecosystems, with target tracking serving as a foundational technology. This paper classifies UAV target tracking into two distinct paradigms: active tracking and passive tracking, differentiated by their operational scopes and technical objectives. Active tracking is defined as a closed-loop spatial pursuit system, whereby UAVs dynamically track targets through iterative cycles centered on three primary stages: online passive tracking, state fusion estimation, and tracking strategy generation, with subsequent execution phases implied in the loop. This workflow bridges perception and action, enabling spatial engagement through continuous sensor-to-control feedback. In contrast, passive tracking acts as a vision-centric analytical module that exclusively extracts target image-domain attributes from visual sensors—devoid of physical state inference or control mechanisms. As a preprocessing stage for active systems, it is constrained to the visual perception layer, lacking the spatial engagement capabilities inherent in closed-loop tracking systems. This paper conducts an in-depth analysis of the application, key challenges, and future trends in both active and passive UAV target tracking. By systematically discussing the relationships among relevant technologies, this work aims to establish a foundational reference framework and offer citation material for guiding the future development of UAV target tracking technologies.

The wing planform and flapping kinematics are critical for the hovering flight of flapping wing micro air vehicles (FWMAVs). The degree of influence of wing geometry and kinematic parameters on aerodynamic performance still lacks in-depth analysis. In this study, a sensitivity analysis was conducted based on the quasi-steady aerodynamic model. Each parameter was investigated independently by using the control variable method. The degree of each variable’s influence on lift, power, and power loading is evaluated and compared. Furthermore, detailed exponential relationships were established between the parameters and the corresponding aerodynamic properties. It is found that, for the geometric parameters, wing area has the greatest influence on lift, and the distribution of area has the most visible effect on aerodynamic power. All geometric parameters are negatively correlated with power loading. For the kinematic parameters, flapping frequency, compared with sweeping amplitude, results in faster lift growth and slower drop in power loading, while their influence on aerodynamic power is nearly comparable. A moderate pitching amplitude with advanced rotation will maximize the lift. For the flapping trajectory, lift and power loading are primarily affected by the shape of the pitching motion rather than the sweeping motion. But the sweeping motion seems to dominate the power consumption. The research in this paper is helpful to understand the effect of each parameter and provide theoretical guidance for the development of FWMAVs.

Flying vertebrates use specialized wingbeat kinematics in hovering, takeoff, and landing, featuring ventrally anterior downstrokes and aerodynamically inactive upstrokes to enhance aerodynamic characteristics at low airspeeds. Rarely implemented in robotics, this inspired RoboFalcon2.0, a flapping-wing robot with reconfigurable mechanisms performing bioinspired flap-sweep-fold (FSF) motion for controlled bird-style takeoff. FSF couples flapping, sweeping, and folding within a single wingbeat cycle, mimicking vertebrate slow-flight kinematics. Wind tunnel tests demonstrate that sweeping amplitude modulates lift and pitching moment in FSF motion. Computational fluid dynamics simulations reveal that FSF’s aerodynamic effects correlate with leading-edge vortex strength and pressure center location. Dynamics simulations analyze pitch control during takeoff. Real-world flights validate RoboFalcon2.0’s self-takeoff capability. This work advances avian-inspired robotics through vertebrate-like actuation principles, enabling more biomimetic flapping-wing designs.