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Precise prediction of unsteady flapping aerodynamics in insect flight is of potential importance in the analysis of maneuverability and flight control. While the quasi-steady model is a cheap while reasonable tool, accurate evaluation of unsteady dynamic effects in complex flight behaviours remains a challenge. Here we develop a computational fluid dynamics (CFD) data-driven aerodynamic model (CDAM), which is informed by high-fidelity CFD simulations using overset meshes to enable the precise and fast prediction of both cycle-averaged and transient aerodynamic force, torque and power with various flying motions and wing kinematics. The CDAM comprises a quasi-steady model for flapping wings and an aerodynamic model for a moving body. The least square method and a surrogate method are employed to achieve aerodynamic coefficient fitting through training using a CFD database. With comparison to CFD test data, the CDAM is validated to be capable of accurately evaluating the aerodynamic force, torque and power of a wing-body bumblebee model in various flight velocities. A genetic optimization algorithm embedded with CDAM is proposed to determine trimmed states for forward flight through adjusting wing kinematics, indicating that bumblebees likely fly in a minimized mass-specific aerodynamic power consumption. The CDAM is further applied to proportional-derivative-based longitudinal flight control of bumblebee hovering, with the control parameters optimized by Laplace transformation and the root locus method, which is implemented consistently in both CDAM and CFD environments. Our results demonstrate that CDAM provides a versatile tool to achieve fast and precise aerodynamical prediction for flying insects in various flight behaviours.

Flying insects capable of navigating in highly cluttered natural environments can withstand in-flight collisions because of the combination of their low inertia 1 and the resilience of their wings 2 , exoskeletons 1 and muscles. Current insect-scale (less than ten centimetres long and weighing less than five grams) aerial robots 3 – 6 use rigid microscale actuators, which are typically fragile under external impact. Biomimetic artificial muscles 7 – 10 that are capable of large deformation offer a promising alternative for actuation because they can endure the stresses caused by such impacts. However, existing soft actuators 11 – 13 have not yet demonstrated sufficient power density to achieve lift-off, and their actuation nonlinearity and limited bandwidth create further challenges for achieving closed-loop (driven by an input control signal that is adjusted based on sensory feedback) flight control. Here we develop heavier-than-air aerial robots powered by soft artificial muscles that demonstrate open-loop (driven by a predetermined signal without feedback), passively stable (upright during flight) ascending flight as well as closed-loop, hovering flight. The robots are driven by multi-layered dielectric elastomer actuators that weigh 100 milligrams each and have a resonance frequency of 500 hertz and power density of 600 watts per kilogram. To increase the mechanical power output of the actuator and to demonstrate flight control, we present ways to overcome challenges unique to soft actuators, such as nonlinear transduction and dynamic buckling. These robots can sense and withstand collisions with surrounding obstacles and can recover from in-flight collisions by exploiting material robustness and vehicle passive stability. We also fly two micro-aerial vehicles simultaneously in a cluttered environment. They collide with the wall and each other without suffering damage. These robots rely on offboard amplifiers and an external motion-capture system to provide power to the dielectric elastomer actuators and to control their flight. Our work demonstrates how soft actuators can achieve sufficient power density and bandwidth to enable controlled flight, illustrating the potential of developing next-generation agile soft robots. Heavier-than-air insect-scale aerial robots powered by soft artificial muscles can hover and also recover from in-flight collisions, illustrating the potential for developing next-generation agile soft robots.

[This corrects the article DOI: 10.1371/journal.pone.0134972.].

The coaxial twin-rotor unmanned helicopter features a compact structure, high payload capacity, and efficient hovering performance, making it a highly versatile aircraft with broad application prospects. Traditional coaxial helicopters employ complex gear systems and inner/outer shaft mechanisms to drive the dual rotors, resulting in intricate mechanical structures and control systems that hinder miniaturization and lightweight development. This paper presents a novel compact coaxial twin-rotor foldable unmanned helicopter. The design innovatively adopts dual electric direct-drive motors to power the counter-rotating rotors, significantly simplifying the mechanical transmission while enabling rotor wing folding. A functional prototype has been successfully developed, demonstrating its potential as a military-operations-capable platform for payload deployment.

Response efforts in emergency applications such as border protection, humanitarian relief and disaster monitoring have improved with the use of Unmanned Aerial Vehicles (UAVs), which provide a flexibly deployed eye in the sky. These efforts have been further improved with advances in autonomous behaviours such as obstacle avoidance, take-off, landing, hovering and waypoint flight modes. However, most UAVs lack autonomous decision making for navigating in complex environments. This limitation creates a reliance on ground control stations to UAVs and, therefore, on their communication systems. The challenge is even more complex in indoor flight operations, where the strength of the Global Navigation Satellite System (GNSS) signals is absent or weak and compromises aircraft behaviour. This paper proposes a UAV framework for autonomous navigation to address uncertainty and partial observability from imperfect sensor readings in cluttered indoor scenarios. The framework design allocates the computing processes onboard the flight controller and companion computer of the UAV, allowing it to explore dangerous indoor areas without the supervision and physical presence of the human operator. The system is illustrated under a Search and Rescue (SAR) scenario to detect and locate victims inside a simulated office building. The navigation problem is modelled as a Partially Observable Markov Decision Process (POMDP) and solved in real time through the Augmented Belief Trees (ABT) algorithm. Data is collected using Hardware in the Loop (HIL) simulations and real flight tests. Experimental results show the robustness of the proposed framework to detect victims at various levels of location uncertainty. The proposed system ensures personal safety by letting the UAV to explore dangerous environments without the intervention of the human operator.

This paper describes the results of a six-year project aiming at designing and constructing a flapping twin-wing robot of the size of hummingbird (Colibri in French) capable of hovering. Our prototype has a total mass of 22 g, a wing span of 21 cm and a flapping frequency of 22 Hz; it is actively stabilized in pitch and roll by changing the wing camber with a mechanism known as wing twist modulation. The proposed design of wing twist modulation effectively alters the mean lift vector with respect to the center of gravity by reorganization of the airflow. This mechanism is modulated by an onboard control board which calculates the corrective feedback control signals through a closed-loop PD controller in order to stabilize the robot. Currently, there is no control on the yaw axis which is passively stable, and the vertical position is controlled manually by tuning the flapping frequency. The paper describes the recent evolution of the various sub-systems: the wings, the flapping mechanism, the generation of control torques, the avionics and the PD control. The robot has demonstrated successful hovering flights with an on-board battery for the flight autonomy of 15–20 s.

Ducted fans have been widely used in VTOL aircraft due to the high propulsion efficiency and safety. The efficiency and stability of ducted fans deteriorate in some flight conditions such as hovering in crosswinds or ground effect. It is necessary to optimize the ducted fan’s structures or apply flow control methods for better adaptions to the typical conditions. This paper presents a detailed review on the ducted fan technology for VTOL applications, especially the methods for improving its efficiency and stability. We first simplified the classification categories based on boundary conditions instead of flight conditions, since the new classification method covers more situations and is easier to distinguish flow field characteristics. The flow characteristics, thrust properties and the optimal structures under different boundary conditions were summarized and discussed. Finally, new configurations and flow control methods for increasing the efficiency and stability were introduced. The newly proposed integration design between the ducted fan and the motor was emphasized for increasing the power density of the ducted fans. This review would be helpful to improve our understanding of the relationship between the structures, flow characteristics and thrust properties of ducted fans under different flight conditions, and inspires scientists to design high-efficiency and high-stability propulsion systems with ducted fans.

The design of bionic flapping-wing aircraft, drawing inspiration from birds and insects’ aerodynamic traits and flapping patterns, exhibits distinct advantages at low Reynolds numbers—a limitation of conventional fixed-wing and rotorcraft. Hummingbirds, renowned for their hovering, forward, and backward flight capabilities, inspire military and other applications seeking both performance and concealment. This paper summarizes research progress and key technologies in bionic flapping-wing aircraft, focusing on bird flight mechanisms and the design of hummingbird-mimicking aircraft. Key mechanisms like delayed stall, added mass effect, and wake capture are highlighted. The paper also outlines design considerations and identifies key bottlenecks and future trends in this exciting field.

Shape-morphing systems, which can perform complex tasks through morphological transformations, are of great interest for future applications in minimally invasive medicine 1 , 2 , soft robotics 3 – 6 , active metamaterials 7 and smart surfaces 8 . With current fabrication methods, shape-morphing configurations have been embedded into structural design by, for example, spatial distribution of heterogeneous materials 9 – 14 , which cannot be altered once fabricated. The systems are therefore restricted to a single type of transformation that is predetermined by their geometry. Here we develop a strategy to encode multiple shape-morphing instructions into a micromachine by programming the magnetic configurations of arrays of single-domain nanomagnets on connected panels. This programming is achieved by applying a specific sequence of magnetic fields to nanomagnets with suitably tailored switching fields, and results in specific shape transformations of the customized micromachines under an applied magnetic field. Using this concept, we have built an assembly of modular units that can be programmed to morph into letters of the alphabet, and we have constructed a microscale ‘bird’ capable of complex behaviours, including ‘flapping’, ‘hovering’, ‘turning’ and ‘side-slipping’. This establishes a route for the creation of future intelligent microsystems that are reconfigurable and reprogrammable in situ, and that can therefore adapt to complex situations. A micromachine less than 100 micrometres across, made of arrays of nanomagnets on hinged panels, is encoded with multiple shape transformations  and actuated with a magnetic field.