Christophe De Wagter

Controlled Flight Maneuvers of a Flapping Wing Micro Air Vehicle: a Step Towards the Delfly II Identification

The Delfly II Flapping Wing Micro Air Vehicle was flown in an external tracking chamber. It was possible to perform controlled flight-test maneuvers with an ornithopter that is capable of hover and forward flight, for system identification purposes. This was achieved by programming its autopilot to deflect the a control surface, while keeping the other surfaces at trimmed condition. Step, doublet and triplet inputs of 1/3, 2/3 and 4/3 of a second on the elevator, rudder and flapping frequency actuators were performed to excite the Delfly’s eigenmodes. These tests were carried out at different flight speeds, ranging from -0.5 to 8 m/s and with the ornithopter’s center of gravity at 83%, 74%, 44% and 42% of the wing root chord. As a result, it was possible to cover the Delfly’s flight envelope and collect data that will be used to build a dynamic and aerodynamic model of the Delfly. The selected inputs have shown to excite the Delfly in dampened oscillatory modes that can be compared to phugoid and short period for the longitudinal dynamics. The Delfly is highly affected by the rudder deflections. The results also reveal an unstable lateral mode similar to a spiral.

Stereo Vision Based Obstacle Avoidance on Flapping Wing MAVs

One of the major challenges in robotics is to develop a fly-like robot that can autonomously fly around in unknown environments. State-of-the-art research on autonomous flight of light-weight flapping wing MAVs uses information such as optic flow and appearance variation extracted from a single camera, and has met with limited success. This paper presents the first study of stereo vision for onboard obstacle detection. Stereo vision provides instantaneous distance estimates making the method less dependent than single camera methods on the camera motions resulting from the flapping. After hardware modifications specifically tuned to use on a flapping wing MAV, the computationally efficient Semi-Global Matching (SGM) algorithm in combination with off-board processing allows for accurate real-time distance estimation. Closed-loop indoor experiments with the flapping wing MAV DelFly II demonstrate the advantage of this technique over the use of optic flow measurements.

Autonomous Wind Tunnel Free-Flight of a Flapping Wing MAV

A low-cost high performance control system is developed to enable autonomous untethered flight inside a wind tunnel. Such autonomous flight is desirable for aerodynamic experiments on flapping wing MAVs, since fixing the fuselage has been shown to significantly alter wing deformations, air flow and performance on vehicles with a periodically moving fuselage. To obtain autonomous untethered flight, 3D position information is obtained from off-board WiiMote infrared tracking sensors with a total system accuracy of 0.8mm and an update rate of 80Hz in a quarter cubical meter control box. This information is sent to a 1.5 gram onboard autopilot containing communication, inertial measurements as well as onboard infrared tracking of an in-tunnel LED to achieve the high performance control needed to position itself precisely in the wind tunnel flow. Flight tests were performed with the 16 gram flapping wing MAV DelFly II. The achieved control performance is shown to be sufficient for many new research purposes, like researching the influence of a fixed fuselage in flapping wing aerodynamic measurements and obtaining more precise performance characteristics.

Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones

Autonomous flight of pocket drones is challenging due to the severe limitations on on-board energy, sensing, and processing power. However, tiny drones have great potential as their small size allows maneuvering through narrow spaces while their small weight provides significant safety advantages. This paper presents a computationally efficient algorithm for determining optical flow, which can be run on an STM32F4 microprocessor (168 MHz) of a 4 gram stereo-camera. The optical flow algorithm is based on edge histograms. We propose a matching scheme to determine local optical flow. Moreover, the method allows for sub-pixel flow determination based on time horizon adaptation. We demonstrate velocity measurements in flight and use it within a velocity control-loop on a pocket drone.

Obstacle Avoidance Strategy using Onboard Stereo Vision on a Flapping Wing MAV

The development of autonomous lightweight MAVs, capable of navigating in unknown indoor environments, is one of the major challenges in robotics. The complexity of this challenge comes from constraints on weight and power consumption of onboard sensing and processing devices. In this paper, we propose the “Droplet” strategy, an avoidance strategy based on stereo vision inputs that outperforms reactive avoidance strategies by allowing constant speed maneuvers while being computationally extremely efficient, and which does not need to store previous images or maps. The strategy deals with nonholonomic motion constraints of most fixed and flapping wing platforms, and with the limited field-of-view of stereo camera systems. It guarantees obstacle-free flight in the absence of sensor and motor noise. We first analyze the strategy in simulation, and then show its robustness in real-world conditions by implementing it on a 20-gram flapping wing MAV.

A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns

Flying fast and free Insect flight can be fast and agile, making it hard to study its detailed aerodynamics. Karásek et al. designed an untethered, flapping-wing robot with impressive agility that can mimic fruitfly maneuvers (see the Perspective by Ruffier). They studied the robots motion during rapid banked turns, which revealed that passive motion through the turn generated yaw torque coupling. This correcting yaw rotation propelled the robot toward the escape heading needed for effective turning. Science, this issue p. 1089; see also p. 1073 An untethered, flapping-wing robot with impressive agility is capable of mimicking maneuvers of the fruitfly. Insects are among the most agile natural flyers. Hypotheses on their flight control cannot always be validated by experiments with animals or tethered robots. To this end, we developed a programmable and agile autonomous free-flying robot controlled through bio-inspired motion changes of its flapping wings. Despite being 55 times the size of a fruit fly, the robot can accurately mimic the rapid escape maneuvers of flies, including a correcting yaw rotation toward the escape heading. Because the robot’s yaw control was turned off, we showed that these yaw rotations result from passive, translation-induced aerodynamic coupling between the yaw torque and the roll and pitch torques produced throughout the maneuver. The robot enables new methods for studying animal flight, and its flight characteristics allow for real-world flight missions.

Control of a hybrid helicopter with wings

This work investigates the design parameters and their consequences in the control of a helicopter rotor combined with a pair of fixed wings. This hybrid vehicle has a light and aerodynamically efficient rotor with a large range of pitch angles to enable both hover and forward flight. Because of the light stiff rotor and heavy wings, the hybrid vehicle exhibits couplings between the roll and pitch axes during hover flight. The rotor-wing interaction depends on a lot of parameters. In this article, we utilize a simplified theoretic model and simulations in order to gain insight in the effect of these parameters on the vehicle dynamics. Finally, a controller is designed that compensates undesired coupling between pitch and roll.

Self-supervised monocular distance learning on a lightweight micro air vehicle

Obstacle detection by monocular vision is challenging because a single camera does not provide a direct measure for absolute distances to objects. A self-supervised learning approach is proposed that combines a camera and a very small short-range proximity sensor to find the relation between the appearance of objects in camera images and their corresponding distances. The method is efficient enough to run real time on a small camera system that can be carried onboard a lightweight MAV of 19 g. The effectiveness of the method is demonstrated by computer simulations and by experiments with the real platform in flight.

Design, control, and visual navigation of the DelftaCopter VTOL tail-sitter UAV

To participate in the Outback Medical Express UAV Challenge 2016, a vehicle was designed and tested that can autonomously hover precisely, takeoff and land vertically, fly fast forward efficiently, and use computer vision to locate a person and a suitable landing location. The vehicle is a novel hybrid tail‐sitter combining a delta‐shaped biplane fixed‐wing and a conventional helicopter rotor. The rotor and wing are mounted perpendicularly to each other,and the entire vehicle pitches down to transition from hover to fast forward flight where the rotor serves as propulsion. To deliver sufficient thrust in hover while still being efficient in fast forward flight, a custom rotor system was designed. The theoretical design was validated with energy measurements, wind tunnel tests, and application in real‐world missions. A rotor‐head and corresponding control algorithm were developed to allow transitioning flight with the nonconventional rotor dynamics that are caused by the fuselage rotor interaction. Dedicated electronics were designed that meet vehicle needs and comply with regulations to allow safe flight beyond visual line of sight. Vision‐based search and guidance algorithms running on a stereo‐vision fish‐eye camera were developed and tested to locate a person in cluttered terrain never seen before. Flight tests and a competition participation illustrate the applicability of the DelftaCopter concept.

Characterizing UAS collision consequences in future UTM

UAS will be integrated into the airspace in the near future, but the risk of UAS collision is not well understood which hampers the development of adequate regulations and standards. As risk has two constituents: frequency and consequence, collision risk analysis of UAS operations in future UTM asks for a quantitative assessment of various types of frequency and consequence. However, prior to studying such quantitative assessment, it is a prerequisite to identify the various types of collisions and consequences. Doing the latter is the objective of this paper. This paper follows a step-wise approach in identifying the various types of collision consequence under a given UTM ConOps, focusing on the very-low-level UAS operations. The first steps address the analysis of the UTM ConOps, rules, and infrastructure considered, and the identification of types of objects and UASs that will operate in the very-low-level UTM system. The follow-up steps are to characterize impact materials by applying zone of impact analysis, followed by analyzing the types of collision consequence. The result is a systematic identification and characterization of types of collision consequences as well as applicable impact materials and conditions that will form the basis for safety risk analysis in follow-on research.