he real-world application of Micro Air Vehicles (MAVs) is often constrained by their limited flight range and endurance, primarily due to battery limitations. One way to overcome this challenge is by leveraging naturally occurring vertical air currents, a technique inspired by soaring birds. This paper introduces Osprey Simulator, a framework designed to simulate and test energy-efficient soaring flight strategies for fixed-wing drones. Built on Isaac Sim, Osprey Simulator enables the creation of both randomly generated urban environments and real-world environments, such as the TU Delft campus. These environments are paired with accurate wind field simulations using OpenFOAM, providing a robust platform for studying aerodynamic interactions in diverse settings. This functionality allows for the generation of scalable synthetic datasets, including depth images and wind field information, enabling comprehensive exploration of soaring potential across various structural geometries and wind conditions. Using generated synthetic data, a neural network was trained to predict optimal soaring regions by analyzing depth images and wind field information. The network demonstrates the ability to identify updraft and downdraft regions, enabling more efficient path planning for drones in urban environments. By integrating realistic simulations and advanced predictive models, Osprey Simulator serves as a powerful tool for advancing autonomous soaring and extending the operational range of fixed-wing MAVs.

Prolonging the endurance of fixed-wing UAVs is crucial for achieving complex missions, yet their limited battery life poses a significant challenge. In response, this research proposes a novel approach to extend the endurance of fixed-wing UAVs by enabling autonomous soaring in an orographic wind field. The goal of our research is to develop a controller that can identify feasible soaring regions and autonomously maintain position control without using any throttle. Soaring flight is desirable as it results in a low energy cost with zero throttle usage. However, without throttle usage, the longitudinal motion of the UAV is an under-actuated system, presenting control challenges. The concept of a target gradient line (TGL) is introduced as part of the control algorithm that addresses these challenges and autonomously finds the equilibrium soaring position where sink rate and updraft are in equilibrium. Experimental tests showed promising results, demonstrating the controller’s effectiveness in maintaining autonomous soaring flight in a non-static wind field. We also demonstrate a single degree of control freedom in the soaring position through manipulation of the TGL.

Applications of Unmanned Aerial Vehicles (UAV's) are often limited by flight endurance. To address the limitation of endurance, we propose a regenerative soaring method in this paper. The atmospheric energy from updrafts generated by obstacles such as hills and ships can be harvested by UAV's using a regenerative electric drivetrain. With fixed-wing aircraft, the vehicle can hover with specific wind conditions, and the battery can be recharged in the air while wind hovering. In order to research the feasibility of this regenerative soaring method, we present a model to estimate hovering locations and the amount of extractable power using the proposed method. The resulting modular regeneration simulation tool can efficiently determine the possible hovering locations and provide an estimate of the power regeneration potential for each hovering location, given the UAV's aerodynamic characteristics and wind-field conditions. Furthermore, a working regenerative drivetrain test setup was constructed and characterised that showcased promising conversion efficiencies and can be incorporated into existing UAV's easily.

This research presents the derivation, implementation and safety assessment of a velocity obstacle- based conflict resolution method to be used by UAVs flying within a horizontally restricted airspace by a geofence under the presence of wind. Two parameters indicating the safety of the applied conflict resolution method have been measured, i.e., the Intrusion Prevention Rate (IPR) and the Violation Prevention Rate of the Geofence (VPRG). Three coordination rule-sets have been implemented i.e., 1) geometric optimum (OPT), 2) geometric optimum from target heading (DEST) and 3) only change in heading (HDG). These rule-sets have been assessed during a safety assessment. It was concluded that the OPT rule-set performed best in terms of the IPR and the DEST rule-set performed best in terms of the VPRG under windy and wind calm conditions. The HDG rule-set performed worst in terms of both safety parameters. It was noted that both safety parameters are the lowest when conflicts occur close the geofence under windy conditions for all implemented rule-sets.

Increasing endurance is a major challenge for battery-powered aerial vehicles. A method is presented which makes use of an updraft around obstacles to decrease the power consumption of a fixed-wing, unmanned aerial vehicle. Simulatory results have shown the conditions that the flight controller can fly in.
The effect of a change in wind velocity, wind direction and updraft has been analysed. The simulations showed that an increase in either updraft or absolute wind direction decrease the throttle consumption.
A change in wind velocity results in a shift of the flight controller’s boundaries. The simulations achieved sustained flight at 0 per cent throttle. The practical, autonomous tests reduced the average throttle down to 4.5 per cent in front of the boat. The unfavourable wind conditions and inaccuracies explain this minor
throttle requirement during the final experiment.

In the near future many tasks could be performed by swarms of flying robots. To successfully implement multiple of these swarms in the same airspace they will have to be decentralised, autonomously cope with high densities and even resolve conflicting objectives of other swarms, while remaining controllable by operators through high-level objectives. This article introduces a novel swarming approach dubbed "Velocity Templates" based on artificial potential fields. These global fields represent the objectives of the swarm, which are balanced with local interaction. Different fields are considered leading to still or sustained motion swarms where conflicting objectives between sub-groups or multiple swarms are gracefully resolved. The approach is implemented on groups of 2 and 4 Parrot Bebop UAVs, using an efficient on-board vision algorithm to locate neighbours and a motion tracking system for guidance. The experiments show promising results for further outdoor tests assessing the scalability of the proposed approach.

The goal of the thesis was to establish and validate a model for maneuvering fruit fly flight. Fruit flies are capable of rapidly changing direction and accelerating away from a threat during so-called escape maneuvers. The maneuverability and control of these escape maneuvers are of interest for the development of small unmanned aircraft (Micro Aerial Vehicles) and for the field of neurobiology where the wing kinematic response of fruit flies on visual stimuli is heavily studied.

The group was assigned to design a swarm of hybrid micro air vehicles to compete in the IMAV 2013 outdoors competition. The swarm should be able to perform several mission elements and cooperate within the swarm.

Flapping wing flight has attracted increased interest among aerodynamics researchers recently in view of the recent expansion of design efforts in the field of Micro Aerial Vehicles (MAVs). MAVs are given specific attention because of their potential as mobile platforms capable of reconnaissance and gathering intelligence in hazardous and physically inaccessable areas. To achieve these missions, they should be manoevring with ease, staying aloft and propelling themselves efficiently. Conventional means of aerodynamic force generation are found lacking at this point and the apping-wing approach becomes an appealing or even necessary solution. In contrast to the conventional (fixed and rotary wing) force generation mechanisms, apping wing systems take benefit from the unsteady ow effects that are associated to the vortices separating from the wing leading and trailing edges, which create low pressure regions around the wings that lead to the generation of higher lift and thrust.