Flight Of Micro Aerial Vehicles Research Articles

Sunlight-powered sustained flight of an ultralight micro aerial vehicle.

Limited flight duration is a considerable obstacle to the widespread application of micro aerial vehicles (MAVs)1-3, especially for ultralightweight MAVs weighing less than 10 g, which, in general, have a flight endurance of no more than 10 min (refs. 1,4). Sunlight power5-7 is a potential alternative to improve the endurance of ultralight MAVs, but owing to the restricted payload capacity of the vehicle and low lift-to-power efficiency of traditional propulsion systems, previous studies have not achieved untethered sustained flight of MAVs fully powered by natural sunlight8,9. Here, to address these challenges, we introduce the CoulombFly, an electrostatic flyer consisting of an electrostatic-driven propulsion system with a high lift-to-power efficiency of 30.7 g W-1 and an ultralight kilovolt power system with a low power consumption of 0.568 W, to realize solar-powered sustained flight of an MAV under natural sunlight conditions (920W m-2). The vehicle's total mass is only 4.21 g, within 1/600 of the existing lightest sunlight-powered aerial vehicle6.

Gramian-Aware Control Approach for Atmospheric Gust Harvesting

Micro-aerial vehicles (MAVs) lack the endurance times demanded by typical mission applications, and previous work to minimize flight path disturbances has also quantified their high atmospheric sensitivities. This study introduces an approach to modulate the sensitivity through real-time parameter variation that translates into a net energy gain of the vehicle. By applying a control-theoretic disturbance sensitivity framework and observability gramian via a “gust capture metric,” the formulation modulates vehicle gust response to sensed favorable (or unfavorable) vertical gusts. The approach is implemented in a nonlinear simulation and an experimental test environment for a representative 21 g MAV. These results include the development of a system-identified MAV flight dynamics model and the development of an experimental facility to provide automated, repeatable indoor flight tests over a gust field. Nonlinear model simulation indicates that the control law provides altitude gain over an idealized gust field, consistent with theoretical analysis. The experimental flight facility was equipped with a gust field generation capability, and its velocity and turbulence intensity distribution was quantified. The experimental flight tests evaluating altitude gain under vehicle controller modification show agreement with theoretical and simulation results and indicate the importance of turbulence distribution in atmospheric gust harvesting experiments.

Autonomous navigation of micro aerial vehicles using high-rate and low-cost sensors

The combination of visual and inertial sensors for state estimation has recently found wide echo in the robotics community, especially in the aerial robotics field, due to the lightweight and complementary characteristics of the sensors data. However, most state estimation systems based on visual-inertial sensing suffer from severe processor requirements, which in many cases make them impractical. In this paper, we propose a simple, low-cost and high rate method for state estimation enabling autonomous flight of micro aerial vehicles, which presents a low computational burden. The proposed state estimator fuses observations from an inertial measurement unit, an optical flow smart camera and a time-of-flight range sensor. The smart camera provides optical flow measurements up to a rate of 200 Hz, avoiding the computational bottleneck to the main processor produced by all image processing requirements. To the best of our knowledge, this is the first example of extending the use of these smart cameras from hovering-like motions to odometry estimation, producing estimates that are usable during flight times of several minutes. In order to validate and defend the simplest algorithmic solution, we investigate the performances of two Kalman filters, in the extended and error-state flavors, alongside with a large number of algorithm modifications defended in earlier literature on visual-inertial odometry, showing that their impact on filter performance is minimal. To close the control loop, a non-linear controller operating in the special Euclidean group SE(3) is able to drive, based on the estimated vehicle’s state, a quadrotor platform in 3D space guaranteeing the asymptotic stability of 3D position and heading. All the estimation and control tasks are solved on board and in real time on a limited computational unit. The proposed approach is validated through simulations and experimental results, which include comparisons with ground-truth data provided by a motion capture system. For the benefit of the community, we make the source code public.

Computational Study of Fluid Flow Behavior Over Bio-Inspired Corrugated Airfoil for Micro Aerial Vehicles

Comprehensive computational fluid dynamic study of bio-inspired corrugated airfoil is performed at low Reynolds number typical of gliding flight of micro aerial vehicles. Two-dimensional computational models of corrugated airfoil and flat plate of same chord length are generated using ANSYS modeling tools. The models are meshed using ICEMCFD with rectangular block meshing. Numerical simulations are performed at Reynolds number of 3.5x104 and angles of attack ranging from -40 to 120. K-e turbulence model is used to implement the turbulent condition in flow domain. The boundary conditions and size of flow domain are taken as per the available experimental data to facilitate future experimental verification. The flow parameters such as velocity and pressure of the corrugated airfoil are obtained computationally and compared with baseline flat plate of same chord length and plate thickness. The flow parameters such as velocity and pressure obtained over the corrugated and flat plate profiles indicate that the corrugated wing outperforms the flat plate aerodynamically. Flow conditions such as formation of leading edge vortex in the first valley of corrugated airfoil and formation of trailing edge vortices at higher angles of attack compared to the flat plate. The corrugated profile produced lower drag, higher lift and hence better aerodynamic efficiency than flat plate.

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors.

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.

Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment

The drift of inertial navigation system (INS) will lead to large navigation error when a low-cost INS is used in microaerial vehicles (MAV). To overcome the above problem, an INS/optical flow/magnetometer integrated navigation scheme is proposed for GPS-denied environment in this paper. The scheme, which is based on extended Kalman filter, combines INS and optical flow information to estimate the velocity and position of MAV. The gyro, accelerator, and magnetometer information are fused together to estimate the MAV attitude when the MAV is at static state or uniformly moving state; and the gyro only is used to estimate the MAV attitude when the MAV is accelerating or decelerating. The MAV flight data is used to verify the proposed integrated navigation scheme, and the verification results show that the proposed scheme can effectively reduce the errors of navigation parameters and improve navigation precision.

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV) operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems) inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO) approach was developed to estimate the MAV’s relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV’s states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments.

Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments

In this paper, we describe trajectory planning and state estimation algorithms for aggressive flight of micro aerial vehicles in known, obstacle-dense environments. Finding aggressive but dynamically feasible and collision-free trajectories in cluttered environments requires trajectory optimization and state estimation in the full state space of the vehicle, which is usually computationally infeasible on realistic timescales for real vehicles and sensors. We first build on previous work of van Nieuwstadt and Murray and Mellinger and Kumar, to show how a search process can be coupled with optimization in the output space of a differentially flat vehicle model to find aggressive trajectories that utilize the full maneuvering capabilities of a quadrotor. We further extend this work to vehicles with complex, Dubins-type dynamics and present a novel trajectory representation called a “Dubins–Polynomial trajectory”, which allows us to optimize trajectories for fixed-wing vehicles. To provide accurate state estimation for aggressive flight, we show how the Gaussian particle filter can be extended to allow laser rangefinder localization to be combined with a Kalman filter. This formulation allows similar estimation accuracy to particle filtering in the full vehicle state but with an order of magnitude more efficiency. We conclude with experiments demonstrating the execution of quadrotor and fixed-wing trajectories in cluttered environments. We show results of aggressive flight at speeds of up to 8 m/s for the quadrotor and 11 m/s for the fixed-wing aircraft.

Application of Unfalsified Control Theory in Controlling MAV

Controlling the flight of Micro Aerial Vehicles (MAV) is a highly challenging task, mostly due to nonlinearity of their models and highly varying longitudinal and lateral derivatives coefficients [. As such, it requires a proper form of robust control. The demand for such control is very high, as it is required in many applications. The following paper presents the application of Unfalsified Control Theory developed by Michael G. Safonov [1, 2, 6, . This interesting approach is based on the adaptive switching control, and does not require any previous knowledge of the controlled plant. The controlled dynamics is decoupled due to longitudinal and lateral motion of the Bell 540 single-delta wing micro aerial vehicle. The work involves design and simulation of the proper robust controller. The simulation is based on already obtained nominal model of the Bell 540 vehicle [. The developed controllers were proved to be efficient, based on performed calculations and simulation in Matlab.

Pitch Control of a Micro Air Vehicle with Micropressure Sensors

Maintaining stable flight of micro aerial vehicles is challenging, especially in complex, low-Reynolds-number flight environments while considering wind gust disturbance, flow separation, and flow reattachment. To date, most micro aerial vehicles use vision, inertial measurement units, and/or global positioning systems as their primary sensing and navigation devices; however, actual flow conditions over the aircraft wing surfaces cannot be captured directly. In this paper, a biologically inspired micro aerial vehicle pitch control system is designed using distributed pressure information. The pressure information on the wing surfaces of a micro aerial vehicle is directly measured by a array of digital barometric micropressure sensors and is then used to calculate the aerodynamic forces, center of pressure, pitching moment, etc. A new pitch motion model that can capture the pressure information is derived from the control perspective. A nonlinear controller is also designed to achieve accurate pitch control, which is robust with respect to bounded uncertainties and unmodeled dynamics. It is anticipated that this new micro aerial vehicle design, which uses real-time sensed pressure information, can significantly enhance the stability and agility of micro aerial vehicles.

Cell Geometry and Material Property Effects on Membrane and Flow Response

TO OPTIMIZE micro aerial vehicle (MAV) designs for size and speed regimes characteristic of small birds and insects, a growing subset of low-Reynolds-number research groups practice biomimetics to take advantage of nature-optimized designs proven effective within the MAV flight regime [1]. One common feature of many natural flyers is wing flexibility. Engineering models that mimic low-Reynolds-number fliers with fixed-wing flexibility have demonstrated improved aerodynamics compared with conventional rigid airfoils. This improvement is attributed to a combination of passive static and dynamic deformations of the flexible-membrane wings supported by semirigid, fixed-wing frames. Static deformation, of bothmembrane and frame, can advantageously affect airfoil camber and tip washout through inflation and alteration of aerodynamic and geometric twist [2–4]. Dynamic membrane deformations can improvemomentum transfer between the leeside free shear layer and recirculation region of models with rigid leading and trailing edges and a membrane attached in between, thereby, decreasing the extent of flow separation and corresponding wake size, as well as advantageously affecting the aerodynamic forces [5,6]. Similar vibrations also exist for membrane wings with an unattached trailing edge. Hubner and Hicks [7] showed aerodynamic efficiency improvement by scalloping the trailing edge and developed scaling trends with respect to cell geometry. Johnston et al. [8] demonstrated via high-speed imagery that membrane prestrain increased flutter onset velocity while reducing the magnitude of the postflutter limit cycle oscillations. A free trailing-edge wing structure typically includes a flat or cambered frame of moderate or low aspect ratio that is significantly less compliant than the attached membrane. The membrane is attached along the leading edge of the frame and along battens (or ribs) extending from the leading edge. In this Note, it is documented that the initial flutter onset frequency of zero-applied-pretension membranes originates from small-amplitude membrane vibrations at the natural frequency of the membrane. Although applied pretensioning will affect the frequency, cell geometry and material properties are shown to play an important role as well. Spectral data from the membrane and the leeside shear layer via simultaneously sampled hot-wire anemometry and laser vibrometry are presented and discussed in this Note.

Nonlinear trajectory control of a flapping‐wing micro aerial vehicle

PurposeThe purpose of this paper is to develop a nonlinear control system for flight trajectory control of flapping Micro Aerial Vehicles (MAVs), subjected to wind.Design/methodology/approachIn the dynamic study and fabrication of the MAV, biomimetic principles are considered as the best inspiration for the MAV's flight as well as design constraints. The blade element theory, which is a two‐dimensional quasi‐steady state method, is modified to consider the effect of MAV's translational and rotational velocity. A quaternion‐based dynamic wrench method is then developed for the dynamic system.FindingsThe flapping flight dynamics is highly nonlinear and the system is under‐actuated, so any linear control strategy fails to meet any desired maneuver for trajectory tracking. In this study, a controller with quaternion‐based feedback linearization method is designed for the dynamical averaged system. It is shown that the original system is bonded to a stable limit cycle with desired amplitude and the controller inputs are bounded.Practical implicationsThe effectiveness of a synthesized controller is proved for the cruse and the Cuban‐8 maneuver.Originality/valueThe authors' major contribution is developing feedback linearization quaternion‐based controller and deriving some essential mathematics for implementing quaternion model in the synthesis of controller. A piezoelectric‐actuated wing model is developed for the control system. Results of cursing and turning modes of the flight indicate the stability of the flight. Finally, an appropriate controller is designed for the Cuban‐8 maneuver so that the MAV would follow the trajectory with a bounded fluctuation.

Micro Air Vehicle Trajectory Planning in Winds

M ICRO aerial vehicles (MAVs) are small aerial vehicles, generallywith dimensions on the order of 1 ft (or 0.3m). Their small sizes often imply that their flight speeds are also small, roughly on the order of 20–60 km=h. MAVs come in a wide variety of forms, such as fixed wing, flapping wing, and rotary wing [1]. They are finding increasingly more applications in such areas as military missions, reconnaissance of hazardous or remote areas, and monitoring of indoor areas. Because of their small sizes and light weights, MAV flight trajectories are significantly susceptible to winds in general. For example, it is possible for the wind to be so strong that the MAV is unable to advance in certain directions. (This problem can be formulated in terms of the controllability of a point and its associated reachable set, see [2].) It is therefore necessary to develop a systematic approach toMAV trajectory generation that addresses the characteristic issues of MAV flights in winds. Specifically, the following three points must be considered: 1) Target points may not always be feasible due to winds. 2) Wind profiles may have significant effects on fuel costs (both desirable and undesirable). 3) Trajectory generation must always yield a feasible solution due to the absence of human operators. The main goal of this note is to study meaningful trajectory generation problem formulations for MAV trajectories in winds, to address all three of the issues discussed above that characterize MAV flights. Specifically, MAV flights in winds are formulated as nonlinear optimal control problems, with proper constraints on states and controls. In particular, the reaching of a target point is enforced via a penalty term in the performance index. Thus, while a target point is not necessarily reached, a flyable trajectory that is optimal under prevailing conditions is obtained. Both constant and position dependent wind is considered.

The Low Reynolds Number Wing Aerodynamics and Micro Aerial Vehicles Development

Micro Aerial Vehicle (MAV) has emerged as an attractive and significant research topic in aeronautical academia in last decade because of its profound applications and complicated aerodyanmics. This paper reports a summary of review about the MAV development and its low Reynolds number wing aerodynamic characteristics (such as instability and evolutional behavior) and vehicle design considerations made in past years in our lab. The most recent progress on optimization of single-winged and cascade-winged MAV design and flight tests is also discussed.

Development of a Fully Autonomous Micro Aerial Vehicle (MAV) for Ground Traffic Surveillance

This paper describes the development of an autonomously operating Micro Aerial Vehicle (MAV) at the Institute of Aerospace Systems, Technical University of Braunschweig, Germany. After presenting the theoretical work on autonomous MAV flight, the currect prototype “Carolo” is introduced, a MAV with a wingspan of 40 cm and a mass of 390 g. One of the main applications for the MAV is ground traffic surveillance, allowing quick and flexible visual information retrieval in real-time. The operational concept is presented as well as the implemented ground control software. The first autonomous flight of “Carolo” is scheduled for autumn 2003.