Erik-Jan Van Kampen

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.

Selective Velocity Obstacle Method for Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicles

Autonomous collision avoidance system (ACAS) for Unmanned Aerial Vehicles (UAVs) is set as a tool to prove that they can achieve the equivalent level of safety, required in context of integrating UAVs flight into the National Airspace System (NAS). This paper focus on the cooperative avoidance part, aiming to define an algorithm that can provide avoidance between cooperative UAVs in general, while still be restricted by some common rules. The algorithm is named the Selective Velocity Obstacle (SVO) method, which is an extension of the Velocity Obstacle method. The algorithm gives guidelines for UAVs to select between three basic modes for avoidance, i.e., to Avoid, Maintain, or Restore. The variation of those three modes gives flexibility for UAVs to choose how will they avoid. By modeling the algorithm as a hybrid system, simulations on various UAVs encounters scenario were conducted and shows satisfying result. Monte Carlo simulations are then conducted to conclude the performance even more. Randomizing the initial parameters, including speed, attitude, positions and avoidance starting point, more than 10 encounter scenario were tested, involving up until five UAVs. A parameter called the Violation Probability is then derived, showing zero violations in the entire encounter samples.

Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicle

Autonomous collision avoidance system (ACAS) was defined and investigated in this paper to support UAVs integration to the national airspace system. This includes not only UAVs on-board system, but also the definition of requirements, collision avoidance structure, and the avoidance rules. This paper focuses on the cooperative avoidance, where UAVs (or any aircraft) involved avoid each other using rules previously agreed by involved parties. A novel algorithm of avoidance was developed, named as Selective Velocity Obstacle (SVO) method. Several simulations were conducted and show satisfying result on how well the algorithm work to avoid separation violations. In the end of the paper, using Monte Carlo simulation, violation probabilities were derived for three setups. These simulations shows the performance of the developed algorithm for cooperative ACAS, and suggesting the need to derive a new parameter, i.e., the minimum required turning rate of avoidance.

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.

Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

This paper proposes a taxonomy of conflict detection and resolution (CD&R) approaches for operating unmanned aerial vehicles (UAVs) in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuvering, and autonomy. The factors are combined back selectively, with regard to their feasibility for operation in an integrated airspace, into several “generic approaches” that form the CD&R taxonomy. These generic approaches are then attributed to a number of available methods in the literature to determine their position in the overall CD&R scheme. The attribution shows that many proposed methods are actually unsuitable for operation in an integrated airspace. Furthermore, some part of the taxonomy does not have an adequate representative in the literature, suggesting the need to concentrate UAV CD&R research more in those particular parts. Finally, a multilayered CD&R architecture is built from the taxonomy, implementing the concept of defense in depth to ensure safe operation of UAVs in an integrated civil airspace.

Three-Dimensional Velocity Obstacle Method for Uncoordinated Avoidance Maneuvers of Unmanned Aerial Vehicles

This paper proposes a novel avoidance method called the three-dimensional velocity obstacle method. The method is designed for unmanned aerial vehicle applications, in particular to autonomously handle uncoordinated multiple encounters in an integrated airspace, by exploiting the limited space in a three-dimensional manner. The method is a three-dimensional extension of the velocity obstacle method that can reactively generate an avoidance maneuver by changing the vehicle velocity vector based on the encounter geometry. Adverse maneuvers of the obstacle are anticipated by introducing the concept of a buffer velocity set, which ensures that the ownship will diverge with sufficient space in case of sudden imminence. A three-dimensional resolution is generated by choosing the right plane for avoidance, in which the unmanned aerial vehicle conducts a pure turning maneuver. Implementation of the three-dimensional velocity obstacle method is tested in several simulations that demonstrate its capability to resol...

Active fault-tolerant control for quadrotors subjected to a complete rotor failure

This paper deals with the active fault-tolerant control for quadrotors which are subjected to a total rotor failure. Previous studies assume that the fault has been detected and isolated and then design a fault-tolerant controller. The present paper proposes a complete active fault-tolerant control system which copes with not only fault detection and isolation but also fault-tolerant control. A novel and efficient fault detection and isolation approach is proposed for the total rotor failure case. An incremental nonlinear dynamic inversion approach is introduced to design the fault-tolerant controller for the quadrotor in the presence of the fault. The complete active fault-tolerant control system enables the quadrotor to achieve any position even after the complete loss of one rotor.

Robustness and Tuning of Incremental Backstepping Approach

Incremental Backstepping (IBS) approach is robust to the uncertainties in the plant dynamics term f(x). However, its robustness to the uncertainties in the control effectiveness term g(x) remains unknown especially in the presence of actuator dynamics. Furthermore, it requires the assumption of the availability of fast actuator dynamics. In this paper, the robustness is analyzed with and without the actuator dynamics. It is found that uncertainties with γ > 1 are advantageous for the stability of the complete system. Then, the tuning of the IBS is introduced. Two methods which can increase the robustness of the IBS are proposed: γ tuning and actuator compensator. The design of an actuator compensator requires the parameter of the actuator whereas the γ tuning methods does not. Finally, the robustness to model uncertainties is verified by simulation examples, which show the effectiveness of the proposed approaches.

Velocity Obstacle Method for Non-cooperative Autonomous Collision Avoidance System for UAVs

Unmanned Aerial Vehicles (UAVs) are required to have Autonomous Collision Avoidance System (ACAS) to resolve conflicts, especially when flying in the National Airspace System (NAS). This paper focused on the non-cooperative concept for avoidance, where UAVs face rogue obstacle that does not cooperatively share their flight data, nor they follows the rule of the air. UAVswill rely on its on-board sensor for avoidance, in space and time range that is limited. The limitation make the entire process of sense, detect, and avoid (SDA) mostly not applicable, and sense and avoid (SA) manner is more preferable and safe. A method called SA-VO that extend the use of the known Velocity Obstacle (VO-) method is introduce to handle the problem. The method produce more efficient avoidance in the non-cooperative space than SA manner of avoidance, without fully run the SDA process. Probability of collision map based on ranges of obstacle range of positions and velocity is predefine to replace the detection part of SDA. The method is then tested using simulations of encounters between UAV and an obstacle. The simulations show that SA-VO can be a middle ground between the SDA and SA manner of avoidance.

Sensor Fault Detection and Estimation for Quadrotors Using Kinematic Equations

This paper proposes a new method for detecting and estimating the faults in the sensors of quadrotor Unmanned Aerial Vehicles. The model used for the fault detection is the kinematic model of the quadrotors, which reduces the influence of model uncertainties. The faults in the sensors are modelled by a random walk process. The state vector of the Unscented Kalman Filter is augmented with the faults, which allows the faults to be estimated. The proposed approach is validated by two scenarios: in the presence and absence of sensor faults. Simulation result shows that the Augmented Unscented Kalman Filter can estimate both the state and faults well, which enables the quadrotor to maintain the flight even in the presence of sensor faults.