Flapping Wing Micro Air Vehicle Research Articles

Acrobatics at the insect scale: A durable, precise, and agile micro–aerial robot

Aerial insects are exceptionally agile and precise owing to their small size and fast neuromotor control. They perform impressive acrobatic maneuvers when evading predators, recovering from wind gust, or landing on moving objects. Flapping-wing propulsion is advantageous for flight agility because it can generate large changes in instantaneous forces and torques. During flapping-wing flight, wings, hinges, and tendons of pterygote insects endure large deformation and high stress hundreds of times each second, highlighting the outstanding flexibility and fatigue resistance of biological structures and materials. In comparison, engineered materials and microscale structures in subgram micro–aerial vehicles (MAVs) exhibit substantially shorter lifespans. Consequently, most subgram MAVs are limited to hovering for less than 10 seconds or following simple trajectories at slow speeds. Here, we developed a 750-milligram flapping-wing MAV that demonstrated substantially improved lifespan, speed, accuracy, and agility. With transmission and hinge designs that reduced off-axis torsional stress and deformation, the robot achieved a 1000-second hovering flight, two orders of magnitude longer than existing subgram MAVs. This robot also performed complex flight trajectories with under 1-centimeter root mean square error and more than 30 centimeters per second average speed. With a lift-to-weight ratio of 2.2 and a maximum ascending speed of 100 centimeters per second, this robot demonstrated double body flips at a rotational rate exceeding that of the fastest aerial insects and larger MAVs. These results highlight insect-like flight endurance, precision, and agility in an at-scale MAV, opening opportunities for future research on sensing and power autonomy.

The Development and Prospect of Micro Air Vehicles

This paper systematically reviews the evolution of Micro Air Vehicle (MAV) aerofoil design, covering the geometric optimization and development from fixed-wing, rotary-wing, and flapping-wing to biomimetic-wing designs. In low Reynolds number environments, there are four main types of fixed-wing aerofoils, considered the classic designs for MAVs and have significantly contributed to the future development of MAV aerofoils. Rotary-wing and flapping-wing MAVs represent the initial application of bionics in aerofoil design. At the same time, the lift mechanisms discovered in insects and birds have since officially introduced MAV aerofoil design into the field of biomimetics. By integrating the locomotion mechanisms of animals such as stingrays and beetles, current research on biomimetic aerofoils has developed deployable and multi-parameter morphing wings Meanwhile, through the fusion of new and traditional technologies, the lift-to-drag ratio and flight efficiency are significantly improved. Finally, the paper summarizes the research methods and future directions of MAV aerofoil design, pointing out that the aerodynamic principles at low Reynolds numbers and the bionic kinematic principles of animals are the current research bottlenecks. These challenges can be addressed through cross-disciplinary research and further experimental validation to optimize MAV aerofoil designs.

Insect-inspired passive wing collision recovery in flapping wing microrobots.

Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive and deformable leading edge, as seen in bumblebees and honeybees. Inspired by the latter, a novel approach has been developed for improving collision recovery in micro aerial vehicles (MAVs) by mimicking the principle of stiffness anisotropy present in the leading edges of these insects. This study introduces a passive, flexible, folding wing design with adaptive leading edges. The impact of these adaptive folding leading edges on the flight performance of flapping-wing MAVs was systematically evaluated. Variations in lift generation and obstacle-crossing capabilities between rigid wings and adaptive deformable wings were quantified. Additionally, the mechanical stiffness of the wings was assessed to validate their functional effectiveness. The proposed mechanism was incorporated into the wings of a dual-layer flapping-wing robot, which demonstrated successful flight recovery after collision. The experimental results indicate that a robot with a 30 cm wingspan can effectively traverse a gap of 16.2cm during flight, thereby demonstrating its enhanced ability to overcome collision challenges. These findings underscore the potential of adaptive wing designs in enhancing the resilience and performance of MAVs in dynamic environments.

Fixed-Time Adaptive Fuzzy Fault-Tolerant Control of Flapping Wing MAVs With Wing Damage

Fixed-Time Adaptive Fuzzy Fault-Tolerant Control of Flapping Wing MAVs With Wing Damage

Hovering of Bi-Directional Motor Driven Flapping Wing Micro Aerial Vehicle Based on Deep Reinforcement Learning

Inspired by hummingbirds and certain insects, flapping wing micro aerial vehicles (FWMAVs) exhibit potential energy efficiency and maneuverability advantages. Among them, the bi-directional motor-driven tailless FWMAV with simple structure prevails in research, but it requires active pose control for hovering. In this paper, we employ deep reinforcement learning to train a low-level hovering strategy that directly maps the drone’s state to motor voltage outputs. To our knowledge, other FWMAVs in both reality and simulations still rely on classical proportional-derivative controllers for pose control. Our learning-based approach enhances strategy robustness through domain randomization, eliminating the need for manually fine-tuning gain parameters. The effectiveness of the strategy is validated in a high-fidelity simulation environment, showing that for an FWMAV with a wingspan of approximately 200 mm, the center of mass is maintained within a 20 mm radius during hovering. Furthermore, the strategy is utilized to demonstrate point-to-point flight, trajectory tracking, and controlled flight of multiple drones.

Unsteady Aerodynamic Forces of Tandem Flapping Wings with Different Forewing Kinematics.

Dragonflies can independently control the movement of their forewing and hindwing to achieve the desired flight. In comparison with previous studies that mostly considered the same kinematics of the fore- and hindwings, this paper focuses on the aerodynamic interference of three-dimensional tandem flapping wings when the forewing kinematics is different from that of the hindwing. The effects of flapping amplitude (Φ1), flapping mean angle (ϕ1¯), and pitch rotation duration (Δtr1) of the forewing, together with wing spacing (L) are examined numerically. The results show that Φ1 and ϕ1¯ have a significant effect on the aerodynamic forces of the individual and tandem systems, but Δtr1 has little effect. At a small L, a smaller Φ1, or larger ϕ1¯ of the forewing can increase the overall aerodynamic force, but at a large L, smaller Φ1 or larger ϕ1¯ can actually decrease the force. The flow field analysis shows that Φ1 and ϕ1¯ primarily alter the extent of the impact of the previously revealed narrow channel effect, downwash effect, and wake capture effect, thereby affecting force generation. These findings may provide a direction for designing the performance of tandem flapping wing micro-air vehicles by controlling forewing kinematics.

Reinforcement Twinning: From digital twins to model-based reinforcement learning

The concept of digital twins promises to revolutionize engineering by offering new avenues for optimization, control, and predictive maintenance. We propose a novel framework for simultaneously training the digital twin of an engineering system and an associated control agent. The training of the twin combines methods from adjoint-based data assimilation and system identification, while the training of the control agent combines model-based optimal control and model-free reinforcement learning. The training of the control agent is achieved by letting it evolve independently along two paths: one driven by a model-based optimal control and another driven by reinforcement learning. The virtual environment offered by the digital twin is used as a playground for confrontation and indirect interaction. This interaction occurs as an “expert demonstrator”, where the best policy is selected for the interaction with the real environment and “cloned” to the other if the independent training stagnates. We refer to this framework as Reinforcement Twinning (RT). The framework is tested on three vastly different engineering systems and control tasks, namely (1) the control of a wind turbine subject to time-varying wind speed, (2) the trajectory control of flapping-wing micro air vehicles (FWMAVs) subject to wind gusts, and (3) the mitigation of thermal loads in the management of cryogenic storage tanks. The test cases are implemented using simplified models for which the ground truth on the closure law is available. The results show that the adjoint-based training of the digital twin is remarkably sample-efficient and completed within a few iterations. Concerning the control agent training, the results show that the model-based and the model-free control training benefit from the learning experience and the complementary learning approach of each other. The encouraging results open the path towards implementing the RT framework on real systems.

Research on insect-like long endurance hovering double-wing FMAV prototype

PurposeEndurance time is an important factor limiting the progress of flapping-wing aircraft. In this study, this paper developed a prototype of a double-wing flapping-wing micro air vehicle (FMAV) that mimics insect-scale flapping wing for flight. Besides, novel methods for optimal selection of motor, wing length and battery to achieve prolonged endurance are proposed. The purpose of this study is increasing the flight time of double-wing FMAV by optimizing the flapping mechanism, wings, power sources, and energy sources.Design/methodology/approachThe 20.4 g FMAV prototype with wingspan of 21.5 cm used an incomplete gear flapping wing mechanism. The motor parameters related to the lift-to-power ratio of the prototype were first identified and analyzed, then theoretical analysis was conducted to analyze the impact of wing length and flapping frequency on the lift-to-power ratio, followed by practical testing to validate the theoretical findings. After that, analysis and testing examined the impact of battery energy density and efficiency on endurance. Finally, the prototype’s endurance duration was calculated and tested.FindingsThe incomplete gear facilitated 180° symmetric flapping. The motor torque constant showed a positive correlation with the prototype’s lift-to-power ratio. It was also found that the prototype achieved the best lift-to-power ratio when using 100 mm wings.Originality/valueA gear-driven flapping mechanism was designed, capable of smoothly achieving 180° symmetric flapping. Besides, factors affecting long-duration flight – motor, wings and battery – were identified and a theoretical flight duration analysis method was developed. The experimental result proves that the FMAV could achieve the longest hovering time of 705 s, outperforming other existing research on double-wing FMAV for improving endurance.

Analysis of the integrated pattern of hoverable flapping wing micro-air vehicle

Flying creatures, such as insects and hummingbirds, display superior flight capabilities that have inspired the development of Flapping-Wing Micro Air Vehicles (FWMAVs). Although these vehicles have achieved certain milestones, integrating subsystems under stringent size, weight, and power (SWaP) constraints poses significant energy and weight management challenges. These vehicles' common patterns and critical differences still need to be clearly understood, indicating that their integrated patterns still need to be defined.To determine the integrated pattern of these aircraft, this study began with analyzing existing data on hover-capable bionic aircrafts. It then formulated a set of indices through the permutation and combination of subsystem parameters. Key indices were identified by examining the universality and specificity of system indices through case studies of aircraft, which helped establish the integrated pattern of FWMAVs.The study revealed certain commonalities in these aircraft; for example, the actuation system, comprising the drive, transmission, and manipulation systems, accounts for 51.72 % of the take-off weight. Combining the transmission system and structure, the airframe system represents 27.62 % of the take-off weight. The battery system accounts for about 20.18 %, while the electronic system usually constitutes 12.78 % of the aircraft's take-off weight. Additionally, significant variability was observed among aircrafts in parameters such as CD_5 and CD_7, which represent the distribution of control functions, and CS_4, which tests the integration of the structure with the transmission system. This paper constructs an integrated pattern for such aircraft based on these findings.The integrated pattern derived from this work provides a practical range of parameter values for subsystems during the initial design phase of these aircraft. This is crucial for enhancing the iterative convergence speed in engineering, facilitating the parallel development and design of subsystems, and validating the practicality of numerical optimization results from optimization algorithms. Ultimately, this contributes to advancing future designs and developments of hover-capable bio-inspired flying aircraft.

Investigating the Mechanical Performance of Bionic Wings Based on the Flapping Kinematics of Beetle Hindwings.

The beetle, of the order Coleoptera, possesses outstanding flight capabilities. After completing flight, they can fold their hindwings under the elytra and swiftly unfold them again when they take off. This sophisticated hindwing structure is a result of biological evolution, showcasing the strong environmental adaptability of this species. The beetle's hindwings can provide biomimetic inspiration for the design of flapping-wing micro air vehicles (FWMAVs). In this study, the Asian ladybird (Harmonia axyridis Pallas) was chosen as the bionic research object. Various kinematic parameters of its flapping flight were analyzed, including the flight characteristics of the hindwings, wing tip motion trajectories, and aerodynamic characteristics. Based on these results, a flapping kinematic model of the Asian ladybird was established. Then, three bionic deployable wing models were designed and their structural mechanical properties were analyzed. The results show that the structure of wing vein bars determined the mechanical properties of the bionic wing. This study can provide a theoretical basis and technical reference for further bionic wing design.

Aerodynamics of a flapping wing with stroke deviation in forward flight

In this paper, we numerically studied the effect of stroke deviation on the aerodynamic performance of the three-dimensional flapping wing in forward flight at a low Reynolds number. Six deviation motion patterns with different stroke deviation amplitudes were investigated. The results show that the distinct patterns exert a substantial influence on the aerodynamic forces of the flapping wing, with a more pronounced effect at higher values of deviation amplitude. For most patterns, stroke deviation enhances either lift or thrust performance unilaterally. The maximum lift and thrust of the wing with deviation motion can be 37% and 35% larger than that of the wing without deviation motion. A detailed analysis of typical flow characteristics underscores the pivotal role of deviation motion in aerodynamic force generation. Finally, two artificially created innovative deviation motion patterns are proposed, which exhibit an exceptional capacity to augment thrust by up to 123% or enhance comprehensive aerodynamic performance significantly. These findings establish a theoretical foundation for designing high-performance flapping-wing micro-air vehicles.

Analysis of aerodynamic characteristics of flexible flapping wings mimicking hummingbirds

Over hundreds of millions of years of natural selection, hummingbirds have evolved excellent flight characteristics. This ingenious wing structure provides a new inspiration for the design of bionic flapping wings. In this paper, a kind of bionic flexible flapping wing is designed with a hummingbird as the prototype, its parametric aerodynamic characteristics are analyzed, and its feasibility is verified by simulation. Combined with the simulation results, the aerodynamic parameters such as lift, drag, and lift-drag ratio are comprehensively considered, and the optimal parameter combination is 5 m/s-20 Hz. Under this parameter combination, the aerodynamic performance is the best, and the lift-drag ratio is as high as 13.3. This paper can provide a theoretical basis and technical reference for further development of bionic flapping wing MAV design.

Surrogate-based pneumatic and aerodynamic allocation design optimization for flapping-wing micro air vehicles

Determining the mapping relationships between the bionic structures and aerodynamic characteristics of flapping-wing micro air vehicles (FWMAVs), therefore optimizing their comprehensive performances of pneumatic functions and maneuvering capabilities, poses a formidable challenge. In this work, a surrogate-based approach is proposed to tackle the pivotal challenges. Firstly, an experimental surrogate model is established for predicting the pneumatic performances of the flapping wings using multi-fidelity datasets, which incorporates an efficient global optimization strategy for the sample fill-in to enhance predictive precision while minimizing experimental costs. Secondly, to account for the intricate influences of control inputs on aerodynamic characteristics, comprehensive aerodynamic surrogate models are established to precisely anticipate pneumatic performances and torque allocations under different attitude control patterns. Thirdly, by elucidating the mapping relationships between bionic structures and aerodynamic performances, surrogate-based optimizations aim to identify optimal combinations of corresponding parameters of bionic structures, thereby enhancing the pneumatic and toque allocations of the FWMAV. The bionic structures achieve a maximum lift enhancement of 11.5 % and at least a 5.4 % improvement in torque generation through experimental validations. Based on the optimal outcomes of the bionic structure analysis of the FWMAV, a novel prototype family comprising three distinct sub-varieties is successfully fabricated. The findings of our research are hopefully to offer valuable insights for future FWMAV designs and make potential contributions to the advancement of standardized methodologies for evaluating their flight performances.

HiFly-Dragon: A Dragonfly Inspired Flapping Flying Robot with Modified, Resonant, Direct-Driven Flapping Mechanisms

This paper describes a dragonfly-inspired Flapping Wing Micro Air Vehicle (FW-MAV), named HiFly-Dragon. Dragonflies exhibit exceptional flight performance in nature, surpassing most of the other insects, and benefit from their abilities to independently move each of their four wings, including adjusting the flapping amplitude and the flapping amplitude offset. However, designing and fabricating a flapping robot with multi-degree-of-freedom (multi-DOF) flapping driving mechanisms under stringent size, weight, and power (SWaP) constraints poses a significant challenge. In this work, we propose a compact microrobot dragonfly with four tandem independently controllable wings, which is directly driven by four modified resonant flapping mechanisms integrated on the Printed Circuit Boards (PCBs) of the avionics. The proposed resonant flapping mechanism was tested to be able to enduringly generate 10 gf lift at a frequency of 28 Hz and an amplitude of 180° for a single wing with an external DC power supply, demonstrating the effectiveness of the resonance and durability improvement. All of the mechanical parts were integrated on two PCBs, and the robot demonstrates a substantial weight reduction. The latest prototype has a wingspan of 180 mm, a total mass of 32.97 g, and a total lift of 34 gf. The prototype achieved lifting off on a balance beam, demonstrating that the directly driven robot dragonfly is capable of overcoming self-gravity with onboard batteries.

Distributed State Estimation for Flapping-Wing Micro Air Vehicles with Information Fusion Correction.

In this paper, we explore a nonlinear interactive network system comprising nodalized flapping-wing micro air vehicles (FMAVs) to address the distributed H∞ state estimation problem associated with FMAVs. We enhance the model by introducing an information fusion function, leading to an information-fusionized estimator model. This model ensures both estimation accuracy and the completeness of FMAV topological information within a unified framework. To facilitate the analysis, each FMAV's received signal is individually sampled using independent and time-varying samplers. Transforming the received signals into equivalent bounded time-varying delays through the input delay method yields a more manageable and analyzable time-varying nonlinear network error system. Subsequently, we construct a Lyapunov-Krasovskii functional (LKF) and integrate it with the refined Wirtinger and relaxed integral inequalities to derive design conditions for the FMAVs' distributed H∞ state estimator, minimizing conservatism. Finally, we validate the effectiveness and superiority of the designed estimator through simulations.

Maneuvering Characteristics of Bilateral Amplitude-Asymmetric Flapping Motion Based on a Bat-Inspired Flexible Wing.

Flapping-wing micro air vehicles (FWMAVs) have gained much attention from researchers due to their exceptional performance at low Reynolds numbers. However, the limited understanding of active aerodynamic modulation in flying creatures has hindered their maneuverability from reaching that of their biological counterparts. In this article, experimental investigations were conducted to examine the effect of the bilateral amplitude asymmetry of flexible flapping wings. A reduced bionic model featuring bat-like wings is built, and a dimensionless number ΔΦ* is introduced to scale the degree of bilateral amplitude asymmetry in flapping motion. The experimental results suggest that the bilateral amplitude-asymmetric flapping motion primarily induces maneuvering control forces of coupling roll moment and yaw moment. Also, roll moment and yaw moment have a good linear relationship. To achieve more efficient maneuvers based on this asymmetric motion, it is advisable to maintain ΔΦ* within the range of 0 to 0.4. The magnitude of passive pitching deformation during the downstroke is significantly greater than that during the upstroke. The phase of the peak of the passive pitching angle advances with the increase in flapping amplitude, while the valleys lag. And the proportion of pronation and supination in passive pitching motion cannot be adjusted by changing the flapping amplitude. These findings have important practical relevance for regulating turning maneuvers based on amplitude asymmetry and help to understand the active aerodynamic modulation mechanism through asymmetric wing kinematics.

Development of a 2g butterfly-style flapping-wing micro aerial vehicle

A flapping-wing micro aerial vehicle (FMAV) modeled after a butterfly was developed to realize a palm-sized micro aerial vehicle capable of autonomous flight. It has a wingspan of about 220 mm, a weight of 1.8 g with the drive motor and battery installed, and flaps at a frequency of 7 Hz. The results of flight motion analysis using a high-speed camera showed that this butterfly-style FMAV, which does not rely on an external power source and does not have a tail wing, can fly in a straight line while maintaining a constant altitude with an initial speed given. We were also able to observe the flight trajectory of it, which moved up and down with a flapping motion similar to that of a real butterfly. The development of an FMAV that can fly like an insect is important for the viewpoint of robotics to elucidate the posture control mechanism of insects, which still needs to be clarified. The autonomous flight of this butterfly-style FMAV is significant in this regard.

The Aerodynamic Effect of Biomimetic Pigeon Feathered Wing on a 1-DoF Flapping Mechanism.

This study focused on designing a single-degree-of-freedom (1-DoF) mechanism emulating the wings of rock pigeons. Three wing models were created: one with REAL feathers from a pigeon, and the other two models with 3D-printed artificial remiges made using different strengths of material, PLA and PETG. Aerodynamic performance was assessed in a wind tunnel under both stationary (0 m/s) and cruising speed (16 m/s) with flapping frequencies from 3.0 to 6.0 Hz. The stiffness of remiges was examined through three-point bending tests. The artificial feathers made of PLA have greater rigidity than REAL feathers, while PETG, on the other hand, exhibits the weakest strength. At cruising speed, although the artificial feathers exhibit more noticeable feather splitting and more pronounced fluctuations in lift during the flapping process compared to REAL feathers due to the differences in weight and stiffness distribution, the PETG feathered wing showed the highest lift enhancement (28% of pigeon body weight), while the PLA feathered wing had high thrust but doubled drag, making them inefficient in cruising. The PETG feathered wing provided better propulsion efficiency than the REAL feathered wing. Despite their weight, artificial feathered wings outperformed REAL feathers in 1-DoF flapping motion. This study shows the potential for artificial feathers in improving the flight performance of Flapping Wing Micro Air Vehicles (FWMAVs).

Time-history performance optimization of flapping wing motion using a deep learning based prediction model

Flapping Wing Micro Aerial Vehicles (FWMAVs) have caused great concern in various fields because of their high efficiency and maneuverability. Flapping wing motion is a very important factor that affects the performance of the aircraft, and previous works have always focused on the time-averaged performance optimization. However, the time-history performance is equally important in the design of motion mechanism and flight control system. In this paper, a time-history performance optimization framework based on deep learning and multi-island genetic algorithm is presented, which is designed in order to obtain the optimal two-dimensional flapping wing motion. Firstly, the training dataset for deep learning neural network is constructed based on a validated computational fluid dynamics method. The aerodynamic surrogate model for flapping wing is obtained after the convergence of training. The surrogate model is tested and proved to be able to accurately and quickly predict the time-history curves of lift, thrust and moment. Secondly, the optimization framework is used to optimize the flapping wing motion in two specific cases, in which the optimized propulsive efficiencies have been improved by over 40% compared with the baselines. Thirdly, a dimensionless parameter Cvariation is proposed to describe the variation of the time-history characteristics, and it is found that Cvariation of lift varies significantly even under close time-averaged performances. Considering the importance of time-history performance in practical applications, the optimization that integrates the propulsion efficiency as well as Cvariation is carried out. The final optimal flapping wing motion balances good time-averaged and time-history performance.

Design and Flight Performance of a Bio-Inspired Hover-Capable Flapping-Wing Micro Air Vehicle with Tail Wing

A key challenge in flapping-wing micro air vehicle (FWMAV) design is to generate high aerodynamic force/torque for improving the vehicle’s maneuverability. This paper presents a bio-inspired hover-capable flapping-wing micro air vehicle, named RoboFly.S, using a cross-tail wing to adjust attitude. We propose a novel flapping mechanism composed of a two-stage linkage mechanism, which has a large flapping angle and high reliability. Combined with the experimentally optimized wings, this flapping mechanism can generate more than 34 g of lift with a total wingspan of 16.5 cm, which is obviously superior to other FWMAVs of the same size. Aerodynamic force/torque measurement systems are used to observe and measure the flapping wing and aerodynamic data of the vehicle. RoboFly.S realizes attitude control utilizing the deflection of the cross-tail wing. Through the design and experiments with tail wing parameters, it is proved that this control method can generate a pitch torque of 2.2 N·mm and a roll torque of 3.55 N·mm with no loss of lift. Flight tests show that the endurance of RoboFly.S can reach more than 2.5 min without interferences. Moreover, the vehicle can carry a load of 3.4 g for flight, which demonstrates its ability to carry sensors for carrying out tasks.