Efficient Flight Control via Mechanical Impedance Manipulation: Energy Analyses for Hummingbird-Inspired MAVs

Within the growing family of unmanned aerial vehicles (UAV), flapping-wing micro aerial vehicles (MAV) are a relatively new field of research. Inspired by small size and agile flight of insects and birds, these systems offer a great potential for applications such as reconnaissance, surveillance, search and rescue, mapping, etc. Nevertheless, practicality of these vehicles depends on how we address various challenges ranging from control methodology to morphological construction and power supply design. A reasonable approach to resolving such problems is to acquire further inspiration from solutions in nature. Through modeling synchronous muscles in insects, we have shown that manipulation of mechanical impedance properties at wing joints can be a very efficient method for controlling lift and thrust production in flapping-wing MAVs. In the present work, we describe how this approach can be used to decouple lift/thrust regulation, thus reducing the complexity of flight controller. Although of simple design, this controller is still capable of demonstrating a high degree of precision and maneuverability throughout various simulated flight experiments with different types of trajectories. Furthermore, we use these flight simulations to investigate the power requirements of our control approach. The results indicate that these characteristics are considerably lower compared to when conventional control strategies—methods that often rely on manipulating stroke properties such as frequency or magnitude of the flapping motion—are employed. With less power demands, we believe our proposed control strategy is able to significantly improve flight time in future flapping-wing MAVs.     

扑翼飞行的气动建模与仿真分析

用计算流体力学的数值仿真方法对微扑翼飞行的非定常空气动力学问题进行了建模与仿真研究。在对昆虫扑翼飞行运动的仿生模拟基础上，建立了简化的扑翼运动二维翼型的运动学与空气动力学模型。利用任意拉格朗日欧拉（ALE）有限元方法求解出N-S方程的数值解，将流场仿真结果与实验进行了对比，并分析了扑翼运动产生的前缘漩涡对升力的作用。文中的建模、分析方法和结论对微扑翼飞行器的分析设计和应用提供了一定的理论依据。     

Development of a Rotorcraft Micro air Vehicle for Indoor Flight Research

Autonomous flight of micro air vehicles (MAVs) in hostile indoor environments poses significant challenges in terms of control and navigation. In order to support navigation and control research for indoor micro air vehicles, a four-wing tail-sitter type rotorcraft MAV weighing less than 350g has been designed in this paper. In an effort to achieve autonomous indoor flight, an embedded integrated avionic system has been developed. The modeling process has been conducted to obtain accurate six degrees of freedom dynamical model for the designed rotorcraft MAV. In addition, aerodynamic coefficients are evaluated from the results of Computational Fluid Dynamics A PI-ADRC double loop controller with inner-loop outer-loop control scheme has been proposed which takes into account the system’s nonlinearities and uncertainties. The proposed flight controller was implemented on the designed rotorcraft MAV that has undergone various simulation and indoor flight tests. Experimental results that demonstrate robustness of the proposed controller with respect to external disturbances and the capabilities of the designed rotorcraft MAV are presented.     

Study on the structural optimization of a flapping wing micro air vehicle

The development of flapping wing micro air vehicles (MAVs) has yielded remarkable progress over the last decades. Achieving high component stiffness is often in conflict with low weight requirement, which is highly desirable for longer flight time and higher payload. Moreover, vibration originated predominantly from the wings, gears and frames excitations, may compromise the flapping wing MAV’s stability and fatigue life. In order to improve the vehicle’s efficiency and performance, optimization of these various parameters is necessary. In this work, we present the structural optimization of a flapping wing micro air vehicle. We focus particularly on the gearbox optimization using Simulia Tosca Structure in Abaqus, which is a robust tool for designing lightweight, rigid and durable components. Various numerical experiments have been conducted towards optimizing the components’ topology, aimed at increasing the stiffness and reducing weight. The finding and results provide a better understanding of the optimal design topology for a spur gear among other structural components used in MAVs.     

Development and Flight Testing of a Turbulence Mitigation System for Micro Air Vehicles

There are significant challenges associated with the flight control of fixed‐wing micro air vehicles (MAVs) operating in complex environments. The scale of MAVs makes them particularly sensitive to atmospheric disturbances thus limiting their ability to sustain controlled flight. Bio‐inspired, phase‐advanced sensors have been identified as promising sensory solutions for complementing current inertial‐only attitude sensors. This paper describes the development and flight testing of a bio‐inspired, phase‐advanced sensor and associated control system that mitigates the impact of turbulence on MAVs. Multihole pressure probes, inspired by the sensory function of bird feathers, are used to measure the flow pitch angle and velocity magnitude ahead of the MAV's wing. The sensors provide information on the disturbing phenomena before it causes an inertial response in the aircraft. The sensor output is input to a simple feed‐forward control architecture, which enables the MAV to generate a mitigating response to the turbulence. The results from wind‐tunnel and outdoor testing in high levels of turbulence are presented. The disturbance rejection performance of the phase‐advanced sensory system is compared against that of a conventional inertial‐based control system. The developed sensory system shows significant improvement in terms of disturbance rejection performance compared to that of standard inertial‐only control system. It is concluded that a phase‐advanced sensory systems can complement conventional inertial‐based sensors to improve the attitude‐tracking performance of MAVs.     

Inventing a Biologically Inspired, Energy Efficient Micro Aerial Vehicle

In recent years, research efforts have focused on the design, development and deployment of unmanned systems for a variety of applications ranging from intelligence and surveillance to border patrol, rescue operations, etc. Micro Aerial Vehicles are viewed as potential targets that can provide agility and accurate small area coverage while being cost-effective and can be easily launched by a single operator. The small size of MAVs allows such flight operations within confined space but the control effectors must provide sufficient maneuverability, while maintaining stability, with only limited sensing capability onboard the platform. To meet these challenges, researchers have long been attracted by the amazing attributes of biological systems, such as those exhibited by birds and insects. Birds can fly in dense flocks, executing rapid maneuvers with g-loads far in excess of modern fighter aircrafts, and yet never collide with each other, despite the absence of air traffic controllers. This paper introduces a novel framework for the design and control of a Micro Air Vehicle. The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). A sophisticated multi-layered Hybrid & Linear/Non-Linear controller to achieve extended flight times and improved agility compared to other Rotary and Flapping Wing MAV designs. The paper addresses the design and control features of the proposed QV design and gives an overview on the developmental efforts towards the prototyping of the flyer. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance in cluster and swarm formations. The disposable nature of the vehicle would help in battle-field deployment as well, where such a MAV would be made available to soldiers for proximity sensing and threat level assessment. Other applications would include search and rescue operations and civilian law-enforcement.     

微小型飞行器航向系统设计

从实用的角度出发，给出了微小型飞行器的航向系统(包括航向测量和航向控制)体系结构．设计了地磁航向、捷联航向、GPS航向等3种常用的航向测量手段在微小型系统中的实现方案，分析了其各自的优、缺点，提出了一种实用的、基于数据融合的航向获取方法．在航向测量的基础上，又设计了针对微小型飞行器的航向控制方案，并应用于某小型固定翼飞行器的飞行控制系统中．进行了自主飞行试验，取得了预期的试验效果．     

Bio-inspired wing-folding mechanism of micro air vehicle (MAV)

Over the past few years, many researchers have shown an interest in micro air vehicle (MAV), since it can be used for rescue mission and investigation of danger zone which is difficult for human being to enter. In recent years, many researchers try to develop high-performance MAVs, but a little attention has been given to the wing-folding mechanism of wings. When the bird and the flying insects land, they usually fold their wings. If they do not fold their wings, their movement area is limited. In this paper, we focused on the artificial wing-folding mechanism. We designed a new artificial wing that has link mechanism. With the wing-folding mechanism, the wing span was reduced to 15%. In addition, we set feathers separately on the end of wings like those of real birds. The wings make thrust force by the change of the shape of the feathers. However, the wings could not produce enough lift force to lift it. Therefore, we have come to the conclusion that it is necessary to optimize the wings design to get stronger lift force by flapping.     

Longitudinal modelling and control of a flapping-wing micro aerial vehicle

A simulation model, flight-dynamics oriented, of a flapping-wing micro aerial vehicle (MAV) is presented here. The model, based on animal flapping flight, integrates the aerodynamic forces computed along each wing to determine the global motion of the MAV with respect to an inertial reference frame. After some analytic simplifications, and taking into account the periodic nature of the system inputs, an averaged model is derived, and a simple, nonlinear closed-loop control law is designed for the dynamics along the vertical and pitch axis, allowing an efficient stabilization of the naturally unstable model.     

A Biologically-Inspired Micro Aerial Vehicle

This paper introduces a novel framework for the design, modeling and control of a Micro Aerial Vehicle (MAV). The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). We have taken inspiration from the flight mechanism features of the dragonfly and have developed indigenous designs in creating a novel version of a Flapping Wing MAV (FWMAV). The MAV design incorporates a complex mechanical construction and a sophisticated multi-layered, hybrid, linear/non-linear controller to achieve extended flight times and improved agility compared to other rotary wing and FWMAV Vertical Take Off and Landing (VTOL) designs. The first MAV prototype will have a ballpark weight including sensor payload of around 30 g. The targeted lifting capability is about twice the weight. The MAV features state of the art sensing and instrumentation payload, which includes integrated high-power on-board processors, 6DoF inertial sensors, 3DoF compasses, GPS, embedded camera and long-range telemetry capability. A 3-layer control mechanism has been developed to harness the dynamics and attain complete navigational control of the MAV. The inner-layer is composed of a ‘quad hybrid-energy controller’ and two higher layers are at present, implementing a linear controller; the latter will be replaced eventually with a dynamic adaptive non-linear controller. The advantages of the proposed design compared to other similar ones include higher energy efficiency and extended flight endurance. The design features elastic storage and re-use of propulsion energy favoring energy conservation during flight. The design/modeling of the MAV and its kinematics & dynamics have been tested under simulation to achieve desired performance. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance and reconnaissance in cluster and swarm formations. The efficacy of the design is demonstrated through a simulation environment. The dynamics are verified through simulations and a general linear controller coupled with an energy based non-linear controller is shown to operate the vehicle in a stable regime. In accordance with specified objectives a prototype is being developed for flight-testing and demonstration purposes.     

Flapping flight for biomimetic robotic insects: part I-system modeling

This paper presents the mathematical modeling of flapping flight inch-size micro aerial vehicles (MAVs), namely micromechanical flying insects (MFIs). The target robotic insects are electromechanical devices propelled by a pair of independent flapping wings to achieve sustained autonomous flight, thereby mimicking real insects. In this paper, we describe the system dynamic models which include several elements that are substantially different from those present in fixed or rotary wing MAVs. These models include the wing-thorax dynamics, the flapping flight aerodynamics at a low Reynolds number regime, the body dynamics, and the biomimetic sensory system consisting of ocelli, halteres, magnetic compass, and optical flow sensors. The mathematical models are developed based on biological principles, analytical models, and experimental data. They are presented in the Virtual Insect Flight Simulator (VIFS) and are integrated together to give a realistic simulation for MFI and insect flight. VIFS is a software tool intended for modeling flapping flight mechanisms and for testing and evaluating the performance of different flight control algorithms.     

Vision-guided flight stability and control for micro air vehicles

Substantial progress has been made recently towards designing, building and test-flying remotely piloted micro air vehicles (MAVs) and small unmanned air vehicles. We seek to complement this progress in overcoming the aerodynamic obstacles to flight at very small scales with a visionguided flight stability and autonomy system, based on a robust horizon detection algorithm. In this paper, we first motivate the use of computer vision for MAV autonomy, arguing that given current sensor technology, vision may be the only practical approach to the problem. We then describe our statistical vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification. Next, we develop robust schemes for the detection of extreme MAV attitudes, where no horizon is visible, and for the detection of horizon estimation errors, due to external factors such as video transmission noise. Finally, we discuss our feedback controller for selfstabilized flight and report results on vision-based autonomous flights of duration exceeding 10 min. We conclude with an overview of our on-going and future MAV-related research.     

Inertially Aided Visual Odometry for Miniature Air Vehicles in GPS-denied Environments

Unmanned miniature air vehicles (MAVs) have recently become a focus of much research, due to their potential utility in a number of information gathering applications. MAVs currently carry inertial sensor packages that allow them to perform basic flight maneuvers reliably in a completely autonomous manner. However, MAV navigation requires knowledge of location that is currently available only through GPS sensors, which depend on an external infrastructure and are thus prone to reliability issues. Vision-based methods such as Visual Odometry (VO) have been developed that are capable of estimating MAV pose purely from vision, and thus have the potential to provide an autonomous alternative to GPS for MAV navigation. Because VO estimates pose by combining relative pose estimates, constraining relative pose error is the key element of any Visual Odometry system. In this paper, we present a system that fuses measurements from an MAV inertial navigation system (INS) with a novel VO framework based on direct image registration. We use the inertial sensors in the measurement step of the Extended Kalman Filter to determine the direction of gravity, and hence provide error-bounded measurements of certain portions of the aircraft pose. Because of the relative nature of VO measurements, we use VO in the EKF prediction step. To allow VO to be used as a prediction, we develop a novel linear approximation to the direct image registration procedure that allows us to propagate the covariance matrix at each time step. We present offline results obtained from our pose estimation system using actual MAV flight data. We show that fusion of VO and INS measurements greatly improves the accuracy of pose estimation and reduces the drift compared to unaided VO during medium-length (tens of seconds) periods of GPS dropout.     

Modeling and global trajectory tracking control for an over-actuated MAV

This paper deals with an original micro aerial vehicle (MAV) design, the Omnicopter MAV. It has two central coaxial rotors with fixed-pitch propellers and three perimeter mounted ducted fans with servo motors performing thrust vectoring. Compared with traditional rotary wing MAVs that have inherent underactuation, the Omnicopter possesses some advantages in mobility, for example, lateral translation with zero attitude and hover with nonzero attitude. The trajectory tracking control design, global stability analysis, and control allocation are demonstrated through numerical simulation. The advantage of zero attitude translation is illustrated through experimental results.     

扑翼飞行器的多机协同飞行设计与实践

扑翼飞行器(flapping-wing aerial vehicle,FAV)是一种模仿动物飞行方式的新型飞行器,其具有仿生性且飞行声音小等特点,具有广泛的军事和民用前景.由于扑翼飞行器动力学模型复杂且容易受到风等环境因素的影响,目前尚无成熟稳定的控制算法可以用来控制扑翼飞行器.目前对扑翼飞行器的控制大多仍以手动控制为...     

Modeling and Neuro-Fuzzy adaptive attitude control for Eight-Rotor MAV

This paper focuses on modeling and intelligent control of the new Eight-Rotor MAV which is used to solve the problem of low coefficient proportion between lift and gravity for Quadrotor MAV. The dynamical and kinematical modeling for the Eight-Rotor MAV was developed which has never been proposed before. Based on the achieved dynamic modeling, two types of controller were presented. One type, a PID controller is derived in a conventional way with simplified dynamics and turns out to be quite sensitive to sensor noise as well as external perturbation. The second type controller is the Neuro-Fuzzy adaptive controller which is composed of two type-II fuzzy neural networks (TIIFNNs) and one PD controller: The PD controller is adopted to control the attitude, one of the TIIFNNs is designed to learn the inverse model of Eight-Rotor MAV on-line, the other one is the copy of the former one to compensate for model errors and external disturbances, both structure and parameters of T-IIFNNs are tuned on-line at the same time, and then the stability of the Eight-Rotor MAV closed-loop control system is proved using Lyapunov stability theory. Finally, the validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of Neuro-Fuzzy adaptive controller performs very well under sensor noise and external disturbances, and has more superiority than traditional PID controller.     

Robust State and Output Feedback Control of Launched MAVs with Unknown Varying External Loads

The operation of launched micro aerial vehicles (MAVs) with coaxial rotors is usually subject to unknown varying external disturbance. In this paper, a robust controller is designed to reject such uncertainties and track both position and orientation trajectories. A complete dynamic model of coaxial-rotor MAV is firstly established. When all system states are available, a nonlinear state-feedback control law is proposed based on feedback linearization and Lyapunov analysis. Further, to overcome the practical challenge that certain states are not measurable, a high gain observer is introduced to estimate unavailable states and an output feedback controller is developed. Rigid theoretical analysis verifies the stability of the entire closed-loop system. Additionally, extensive simulation studies have been conducted to validate the feasibility of the proposed scheme.     

面向扑翼飞行控制的建模与奇异摄动分析

针对扑翼飞行中的周期性和时标不一现象,以及扑翼飞行实际控制中的问题,本文基于奇异摄动理论,提出了一种针对扑翼周期系统的稳定性分析方法.具体而言,首先建立了扑翼飞行器的多刚体模型,为后文对翅翼动力学的奇异摄动分析铺平道路;其次,对多刚体模型进行简化,抽象出扑翼飞行动力学的核心问题,并针对实际控制中的问题,提出了利用奇异摄...     

Autonomous navigation and environment modeling for MAVs in 3-D enclosed industrial environments

In many applications, the industrial environments are typically 3-D indoor spaces enclosed by shell style structures, which are highly complex with known or unknown non-convex obstacles. GPS signal is unreliable or even unavailable inside, which poses significant technical challenges for the state estimation of micro aerial vehicles (MAVs) performing exploration and modeling tasks in such environments. In this paper, requirements and challenges for 3-D enclosed industrial environments exploration are analyzed firstly, and then state-of-art developments of MAV systems, environment modeling, visual navigation and guidance technologies are reviewed. A robust RGB-D odometry is introduced into the system to provide airborne 6-DOF state estimates of the MAV, which are fused with inertial measurements. Then the fused state information is used to assist the RGB-D based real time 3-D environment modeling. An improved closed-loop RRT based path planning approach (BI-RRT) is developed for information-efficient environment explorations. A flight experimental platform is constructed and the proposed system is validated in flight experiments.     

Vision Based Output Feedback Control of Micro Aerial Vehicles in Indoor Environments

We present a new image based visual servoing (IBVS) approach for control of micro aerial vehicles (MAVs) in indoor environments. Specifically, we show how a MAV can be stabilized and guided using only corridor lines viewed on a front facing camera and angular velocity measurements. Since the suggested controller does not include explicit attitude feedback it does not require the use of accelerometers which are susceptible to vibrations, nor complex attitude estimation algorithms. The controller also does not require direct velocity measurements which are difficult to obtain in indoor environments. The paper presents the new method, stability analysis, simulations and experiments.