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Biomimetics
Special Issues
Bio-Inspired Flight Systems and Bionic Aerodynamics
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Bio-Inspired Flight Systems and Bionic Aerodynamics

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Bioinspired Sensorics, Information Processing and Control".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 19918

Special Issue Editors

Dr. Jiang Zhao

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Interests: flight control; intelligent control; neuromorphic vision sensors; bio-inspired navigation; learning
Special Issues, Collections and Topics in MDPI journals
Dr. Xiangyin Zhang

E-Mail Website
Co-Guest Editor
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Interests: flight systems; bio-inspired computing; bio-inspired robotics; swarm intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Chunhe Hu

E-Mail Website
Co-Guest Editor
The School of Technology, Beijing Forestry University, Beijing 100083, China
Interests: intelligent systems; artificial intelligent; bio-inspired robotics; bio-inspired navigation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To survive in complex and uncertain environments both robustly and efficiently, flight systems have to deal with many challenges, such as modelling and analysis, perception, navigation, planning, maneuvering, communication, and interactive tasks with humans, all in varying environmental conditions. Biomimetic technologies have been employed to advance the development of flight systems, and by mimicking natural creatures, biological principles can be translated into intelligent solutions that focus on improving robustness, adaptability, and cognitive and collaborative functionalities.

This Special Issue aims to exhibit new research achievements, findings and ideas in flight systems that benefit from biomimetic algorithms and methods. Fundamental capabilities can be enhanced, including the design of flight vehicle aerodynamics, the study of deformation motion modes, analysis of wing/rotor/body aerodynamic performance, and other new advances in theoretical, experimental, and computational approaches to bionic aerodynamics applications.

On the other hand, this Special Issue will focus on recent progress in multi-disciplinary biomimetic technologies that have practical potential, such as bio-inspired actuators, neuromorphic vision sensors for perception, biomimetic planning algorithms, bio-inspired learning and control, and biomimetic approaches for human-friendly interaction. To understand and adapt the new principles of bio-inspired solutions to flight systems, some tasks can be also implemented, including GPS-denied navigation, moving object detection and tracking, obstacle and collision avoidance, and swarm intelligence for cooperative flying.

Topics in academic research and industry include but are not limited to:

  • Advances in bionic aerodynamics;
  • Mechanical design of bionic flying vehicles;
  • Bio-inspired sensors and actuators;
  • Bio-inspired motion planning;
  • Bio-inspired learning and control;
  • Bio-inspired autonomous navigation;
  • Applications of bio-inspired flight systems.

Dr. Jiang Zhao
Dr. Xiangyin Zhang
Dr. Chunhe Hu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bio-inspired flight systems
  • bionic aerodynamics
  • sensors
  • actuators
  • motion planning
  • learning
  • control
  • navigation
  • swarm intelligence

Published Papers (10 papers)

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Research

14 pages, 4568 KiB  
Article
Platform Design and Preliminary Test Result of an Insect-like Flapping MAV with Direct Motor-Driven Resonant Wings Utilizing Extension Springs
by Seung-hee Jeong, Jeong-hwan Kim, Seung-ik Choi, Jung-keun Park and Tae-sam Kang
Biomimetics 2023, 8(1), 6; https://doi.org/10.3390/biomimetics8010006 - 23 Dec 2022
Cited by 3 | Viewed by 1758
Abstract
In this paper, we propose a platform for an insect-like flapping winged micro aerial vehicle with a resonant wing-driving system using extension springs (FMAVRES). The resonant wing-driving system is constructed using an extension spring instead of the conventional helical or torsion spring. The [...] Read more.
In this paper, we propose a platform for an insect-like flapping winged micro aerial vehicle with a resonant wing-driving system using extension springs (FMAVRES). The resonant wing-driving system is constructed using an extension spring instead of the conventional helical or torsion spring. The extension spring can be mounted more easily, compared with a torsion spring. Furthermore, the proposed resonant driving system has better endurance compared with systems with torsion springs. Using a prototype FMAVRES, it was found that torques generated for roll, pitch, and yaw control are linear to control input signals. Considering transient responses, each torque response as an actuator is modelled as a simple first-order system. Roll, pitch, and yaw control commands affect each other. They should be compensated in a closed loop controller design. Total weight of the prototype FMAVRES is 17.92 g while the lift force of it is 21.3 gf with 80% throttle input. Thus, it is expected that the new platform of FMAVRES could be used effectively to develop simple and robust flapping MAVs. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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12 pages, 2496 KiB  
Article
Path Planning with Time Windows for Multiple UAVs Based on Gray Wolf Algorithm
by Changchun Zhang, Yifan Liu and Chunhe Hu
Biomimetics 2022, 7(4), 225; https://doi.org/10.3390/biomimetics7040225 - 3 Dec 2022
Cited by 10 | Viewed by 1793
Abstract
The Gray Wolf (GWO) algorithm aims to address the path planning problem of multiple UAVs, and the scene setting is mainly to avoid threats, meet the constraints of UAVs themselves and avoid obstacles between UAVs. The scene setting is relatively simple. To address [...] Read more.
The Gray Wolf (GWO) algorithm aims to address the path planning problem of multiple UAVs, and the scene setting is mainly to avoid threats, meet the constraints of UAVs themselves and avoid obstacles between UAVs. The scene setting is relatively simple. To address such problems, the problem of time windows is considered in this paper, so that the UAV can arrive at the same time, and the Gray Wolf algorithm is used to optimize the problem. Finally, the experimental results verify that the proposed method can plan a safe flight path in the process of multi-UAV flight and reach the goal point at the same time. The mean error of flight time between UAVs of the GWO is 0.213, which is superior to PSO (0.382), AFO (0.315) and GA (0.825). Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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23 pages, 98577 KiB  
Article
Starling-Behavior-Inspired Flocking Control of Fixed-Wing Unmanned Aerial Vehicle Swarm in Complex Environments with Dynamic Obstacles
by Weihuan Wu, Xiangyin Zhang and Yang Miao
Biomimetics 2022, 7(4), 214; https://doi.org/10.3390/biomimetics7040214 - 26 Nov 2022
Cited by 3 | Viewed by 2216
Abstract
For the sake of accomplishing the rapidity, safety and consistency of obstacle avoidance for a large-scale unmanned aerial vehicle (UAV) swarm in a dynamic and unknown 3D environment, this paper proposes a flocking control algorithm that mimics the behavior of starlings. By analyzing [...] Read more.
For the sake of accomplishing the rapidity, safety and consistency of obstacle avoidance for a large-scale unmanned aerial vehicle (UAV) swarm in a dynamic and unknown 3D environment, this paper proposes a flocking control algorithm that mimics the behavior of starlings. By analyzing the orderly and rapid obstacle avoidance behavior of a starling flock, a motion model inspired by a flock of starlings is built, which contains three kinds of motion patterns, including the collective pattern, evasion pattern and local-following pattern. Then, the behavior patterns of the flock of starlings are mapped on a fixed-wing UAV swarm to improve the ability of obstacle avoidance. The key contribution of this paper is collective and collision-free motion planning for UAV swarms in unknown 3D environments with dynamic obstacles. Numerous simulations are conducted in different scenarios and the results demonstrate that the proposed algorithm improves the speed, order and safety of the UAV swarm when avoiding obstacles. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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Graphical abstract

17 pages, 351 KiB  
Article
Modeling and Analysis of a Simple Flexible Wing—Thorax System in Flapping-Wing Insects
by Braden Cote, Samuel Weston and Mark Jankauski
Biomimetics 2022, 7(4), 207; https://doi.org/10.3390/biomimetics7040207 - 21 Nov 2022
Cited by 3 | Viewed by 1748
Abstract
Small-scale flapping-wing micro air vehicles (FWMAVs) are an emerging robotic technology with many applications in areas including infrastructure monitoring and remote sensing. However, challenges such as inefficient energetics and decreased payload capacity preclude the useful implementation of FWMAVs. Insects serve as inspiration to [...] Read more.
Small-scale flapping-wing micro air vehicles (FWMAVs) are an emerging robotic technology with many applications in areas including infrastructure monitoring and remote sensing. However, challenges such as inefficient energetics and decreased payload capacity preclude the useful implementation of FWMAVs. Insects serve as inspiration to FWMAV design owing to their energy efficiency, maneuverability, and capacity to hover. Still, the biomechanics of insects remain challenging to model, thereby limiting the translational design insights we can gather from their flight. In particular, it is not well-understood how wing flexibility impacts the energy requirements of flapping flight. In this work, we developed a simple model of an insect drive train consisting of a compliant thorax coupled to a flexible wing flapping with single-degree-of-freedom rotation in a fluid environment. We applied this model to quantify the energy required to actuate a flapping wing system with parameters based off a hawkmoth Manduca sexta. Despite its simplifications, the model predicts thorax displacement, wingtip deflection and peak aerodynamic force in proximity to what has been measured experimentally in flying moths. We found a flapping system with flexible wings requires 20% less energy than a flapping system with rigid wings while maintaining similar aerodynamic performance. Passive wing deformation increases the effective angle of rotation of the flexible wing, thereby reducing the maximum rotation angle at the base of the wing. We investigated the sensitivity of these results to parameter deviations and found that the energetic savings conferred by the flexible wing are robust over a wide range of parameters. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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18 pages, 6438 KiB  
Article
Deep Reinforcement Learning-Based End-to-End Control for UAV Dynamic Target Tracking
by Jiang Zhao, Han Liu, Jiaming Sun, Kun Wu, Zhihao Cai, Yan Ma and Yingxun Wang
Biomimetics 2022, 7(4), 197; https://doi.org/10.3390/biomimetics7040197 - 11 Nov 2022
Cited by 4 | Viewed by 1675
Abstract
Uncertainty of target motion, limited perception ability of onboard cameras, and constrained control have brought new challenges to unmanned aerial vehicle (UAV) dynamic target tracking control. In virtue of the powerful fitting ability and learning ability of the neural network, this paper proposes [...] Read more.
Uncertainty of target motion, limited perception ability of onboard cameras, and constrained control have brought new challenges to unmanned aerial vehicle (UAV) dynamic target tracking control. In virtue of the powerful fitting ability and learning ability of the neural network, this paper proposes a new deep reinforcement learning (DRL)-based end-to-end control method for UAV dynamic target tracking. Firstly, a DRL-based framework using onboard camera image is established, which simplifies the traditional modularization paradigm. Secondly, neural network architecture, reward functions, and soft actor-critic (SAC)-based speed command perception algorithm are designed to train the policy network. The output of the policy network is denormalized and directly used as speed control command, which realizes the UAV dynamic target tracking. Finally, the feasibility of the proposed end-to-end control method is demonstrated by numerical simulation. The results show that the proposed DRL-based framework is feasible to simplify the traditional modularization paradigm. The UAV can track the dynamic target with rapidly changing of speed and direction. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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24 pages, 2490 KiB  
Article
A Fast-Tracking-Particle-Inspired Flow-Aided Control Approach for Air Vehicles in Turbulent Flow
by Hengye Yang, Gregory P. Bewley and Silvia Ferrari
Biomimetics 2022, 7(4), 192; https://doi.org/10.3390/biomimetics7040192 - 6 Nov 2022
Viewed by 1544
Abstract
Natural phenomena such as insect migration and the thermal soaring of birds in turbulent environments demonstrate animals’ abilities to exploit complex flow structures without knowledge of global velocity profiles. Similar energy-harvesting features can be observed in other natural phenomena such as particle transport [...] Read more.
Natural phenomena such as insect migration and the thermal soaring of birds in turbulent environments demonstrate animals’ abilities to exploit complex flow structures without knowledge of global velocity profiles. Similar energy-harvesting features can be observed in other natural phenomena such as particle transport in turbulent fluids. This paper presents a new feedback control approach inspired by experimental studies on particle transport that have recently illuminated particles’ ability to traverse homogeneous turbulence through the so-called fast-tracking effect. While in nature fast tracking is observed only in particles with inertial characteristics that match the flow parameters, the new fast-tracking feedback control approach presented in this paper employs available propulsion and actuation to allow the vehicle to respond to the surrounding flow in the same manner as ideal fast-tracking particles would. The resulting fast-tracking closed-loop controlled vehicle is then able to leverage homogeneous turbulent flow structures, such as sweeping eddies, to reduce travel time and energy consumption. The fast-tracking approach is shown to significantly outperform existing optimal control solutions, such as linear quadratic regulator and bang-bang control, and to be robust to changes in the vehicle characteristics and/or turbulent flow parameters. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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20 pages, 1602 KiB  
Article
Asymmetric Airfoil Morphing via Deep Reinforcement Learning
by Kelin Lu, Qien Fu, Rui Cao, Jicheng Peng and Qianshuai Wang
Biomimetics 2022, 7(4), 188; https://doi.org/10.3390/biomimetics7040188 - 3 Nov 2022
Cited by 2 | Viewed by 1916
Abstract
Morphing aircraft are capable of modifying their geometry configurations according to different flight conditions to improve their performance, such as by increasing the lift-to-drag ratio or reducing their fuel consumption. In this article, we focus on the airfoil morphing of wings and propose [...] Read more.
Morphing aircraft are capable of modifying their geometry configurations according to different flight conditions to improve their performance, such as by increasing the lift-to-drag ratio or reducing their fuel consumption. In this article, we focus on the airfoil morphing of wings and propose a novel morphing control method for an asymmetric deformable airfoil based on deep reinforcement learning approaches. Firstly, we develop an asymmetric airfoil shaped using piece-wise Bézier curves and modeled by shape memory alloys. Resistive heating is adopted to actuate the shape memory alloys and realize the airfoil morphing. With regard to the hysteresis characteristics exhibited in the phase transformation of shape memory alloys, we construct a second-order Markov decision process for the morphing procedure to formulate a reinforcement learning environment with hysteresis properties explicitly considered. Subsequently, we learn the morphing policy based on deep reinforcement learning techniques where the accurate information of the system model is unavailable. Lastly, we conduct simulations to demonstrate the benefits brought by our learning implementations and validate the morphing performance of the proposed method. The simulation results show that the proposed method provides an average 29.8% performance improvement over traditional methods. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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28 pages, 939 KiB  
Article
Derivative-Free Observability Analysis for Sensor Placement Optimization of Bioinspired Flexible Flapping Wing System
by Bingyu Jin, Hao Xu, Jicheng Peng, Kelin Lu and Yuping Lu
Biomimetics 2022, 7(4), 178; https://doi.org/10.3390/biomimetics7040178 - 26 Oct 2022
Viewed by 1353
Abstract
Observability analysis of a bioinspired flexible flapping wing system provides a measure of how well the states of flexible flapping wing micro-aerial vehicles can be estimated from real-time measurements during high-speed flight. However, the traditional observability analysis approaches have trouble in terms of [...] Read more.
Observability analysis of a bioinspired flexible flapping wing system provides a measure of how well the states of flexible flapping wing micro-aerial vehicles can be estimated from real-time measurements during high-speed flight. However, the traditional observability analysis approaches have trouble in terms of lack of quantitative analysis index, high computational complexity, low accuracy, and unavailability in stochastic systems with memory, including bioinspired flexible flapping wing systems. Therefore, a novel derivative-free observability analysis method is proposed here based on the generalized polynomial chaos expansion. By formulating a surrogate model to represent the relationship between the cumulative measurement and the random initial state, the observability coefficient matrix is calculated and the observability rank condition is stated. Consequently, several observability indices are proposed to quantity the observability of the system. Altogether, the proposed method avoids the disadvantages of the traditional approaches, especially in assessing the observability degree of each state and the effect of stochastic noise on observability. The validation of the proposed method is first provided by demonstrating the equivalence between the traditional and proposed methods and subsequently by comparing the observability of the Lorenz system calculated via three different approaches. Finally, the proposed method is applied on a bioinspired flexible wing system to optimize the placement of sensors, which is consistent with the natural configuration of campaniform sensilla on the wing of the hawkmoth. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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20 pages, 6195 KiB  
Article
REVIO: Range- and Event-Based Visual-Inertial Odometry for Bio-Inspired Sensors
by Yingxun Wang, Bo Shao, Chongchong Zhang, Jiang Zhao and Zhihao Cai
Biomimetics 2022, 7(4), 169; https://doi.org/10.3390/biomimetics7040169 - 18 Oct 2022
Cited by 3 | Viewed by 1573
Abstract
Visual-inertial odometry is critical for Unmanned Aerial Vehicles (UAVs) and robotics. However, there are problems of motion drift and motion blur in sharp brightness changes and fast-motion scenes. It may cause the degradation of image quality, which leads to poor location. Event cameras [...] Read more.
Visual-inertial odometry is critical for Unmanned Aerial Vehicles (UAVs) and robotics. However, there are problems of motion drift and motion blur in sharp brightness changes and fast-motion scenes. It may cause the degradation of image quality, which leads to poor location. Event cameras are bio-inspired vision sensors that offer significant advantages in high-dynamic scenes. Leveraging this property, this paper presents a new range and event-based visual-inertial odometry (REVIO). Firstly, we propose an event-based visual-inertial odometry (EVIO) using sliding window nonlinear optimization. Secondly, REVIO is developed on the basis of EVIO, which fuses events and distances to obtain clear event images and improves the accuracy of position estimation by constructing additional range constraints. Finally, the EVIO and REVIO are tested in three experiments—dataset, handheld and flight—to evaluate the localization performance. The error of REVIO can be reduced by nearly 29% compared with EVIO in the handheld experiment and almost 28% compared with VINS-Mono in the flight experiment, which demonstrates the higher accuracy of REVIO in some fast-motion and high-dynamic scenes. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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13 pages, 4485 KiB  
Article
The Aerodynamic Effect of an Alula-like Vortex Generator on a Revolving Wing
by Ping-Han Chung, Po-Hsiang Chang and Szu-I Yeh
Biomimetics 2022, 7(3), 128; https://doi.org/10.3390/biomimetics7030128 - 10 Sep 2022
Cited by 2 | Viewed by 1958
Abstract
An alula is a small structure of feathers that prevents birds from stalling. In this study, the aerodynamic effect of an alula-like vortex generator (alula-VG) on a revolving wing was investigated using the PIV technique in a water tank. The alula-VG was mounted [...] Read more.
An alula is a small structure of feathers that prevents birds from stalling. In this study, the aerodynamic effect of an alula-like vortex generator (alula-VG) on a revolving wing was investigated using the PIV technique in a water tank. The alula-VG was mounted on a rectangular wing model at two spanwise positions. The wing model with a revolving motion was installed at different angles of attack, which included pre-stall and post-stall conditions. The velocity fields around the wing model with/without an alula-VG were measured and analyzed, including the vorticity contour, the circulation of vortex structures, and the corresponding sectional lift coefficient, which are used to explain the aerodynamic effect induced by an alula-VG. The lift-off and bursting of the leading-edge vortex (LEV) affect the magnitude of the chordwise circulation and the section lift coefficient. The results show that compared to an alula-VG mounted fixed wing model, the flow interactions among the alula-VG induced spanwise flow, the inertial force caused by the revolving motion, and the wing-tip vortex play important roles in the vortex bursting and the resultant aerodynamic performance. The effect of an alula-VG on a revolving wing depends on its spanwise position and the angle of attack of a wing model, which need to be properly matched. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics)
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