Publications

@mastersthesis{uuid:90916a92-95bc-44eb-889e-81555ddd494f,

title = {Microphones as Airspeed Sensors for Micro Air Vehicles},

author = {Momchil Makaveev},

url = {http://resolver.tudelft.nl/uuid:90916a92-95bc-44eb-889e-81555ddd494f},

year  = {2023},

date = {2023-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {This project proposes and evaluates a novel concept for an airspeed instrument aimed at small hybrid unmanned aerial vehicles. The working principle is to relate the power spectra of the wall-pressure fluctuations beneath the turbulent boundary layer formed over the vehicle’s body to its airspeed. The instrument consists of two microphones, flush mounted on the UAV’s nose cone, that capture the pseudo-sound caused by the coherent turbulent structures, and a micro-controller that processes the signals from the microphones and computes the airspeed. Dedicated models were constructed, using data obtained from wind tunnel and flight experiments, that take the power spectra of the microphones’ signals as an input and provide the airspeed as an output. The model structure is a feed-forward neural network with a single hidden layer, trained using a second-order gradient descent algorithm, following a supervised learning approach. The models were validated using only flight data, with the best one achieving a mean approximation error of 0.043 m/s and having a standard deviation of 1.039 m/s. It was also shown that the airspeed could be successfully predicted for a wide range of angles of attack, given that they are known, thus necessitating the vehicle to be equipped with a dedicated angle of attack sensor.},

note = {Smeur, E.J.J. (mentor); Delft University of Technology (degree granting institution)},

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pubstate = {published},

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@mastersthesis{uuid:f5c8a6b4-a43b-43f1-9a2d-72d850515369,

title = {Frustumbug: a 3D Mapless Stereo-Vision-based Bug Algorithm for Micro Air Vehicles},

author = {Ruben Meester},

url = {http://resolver.tudelft.nl/uuid:f5c8a6b4-a43b-43f1-9a2d-72d850515369},

year  = {2023},

date = {2023-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {We present a computationally cheap 3D bug algorithm for drones, using stereo vision. Obstacle avoidance is important, but difficult for robots with limited resources, such as drones. Stereo vision requires less weight and power than active distance measurement sensors, but typically has a limited Field of View (FoV). In addition, the stereo camera is fixed on the drone, preventing sensor movement. For obstacle avoidance, bug algorithms require few resources. We base our proposed algorithm, Frustumbug, on the Wedgebug algorithm, since this bug algorithm copes with a limited FoV. Since Wedgebug only focuses on 2D problems, the Local-epsilon-Tangent-Graph (LETG) is used to extend the path planning to 3D. Disparity images are obtained through an optimised stereo block matching algorithm. Obstacles are expanded in disparity space to obtain the configuration space. Furthermore, Frustumbug has an improved robustness to noisy range sensor data, and includes reversing, climbing and descending manoeuvres to avoid or escape local minima. The algorithm has been extensively tested with 225 flights in two challenging simulated environments, with a success rate of 96%. Here, 3.6% did not reach the goal and 0.4% collided. Frustumbug has been implemented on a 20 gram stereo vision system, and guides drones safely around obstacles in the real world, showing its potential for small drones to reach their targets fully autonomously.},

note = {de Croon, G.C.H.E. (mentor); van Dijk, Tom (mentor); de Wagter, C. (graduation committee); Verhoeven, C.J.M. (graduation committee); Delft University of Technology (degree granting institution)},

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pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:3e922cc4-83a0-43aa-a223-a67e554d2e92,

title = {Deep Vision-based Relative Localisation by Monocular Drones},

author = {Raoul Mink},

url = {http://resolver.tudelft.nl/uuid:3e922cc4-83a0-43aa-a223-a67e554d2e92},

year  = {2023},

date = {2023-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Decentralised drone swarms need real time collision avoidance, thus requiring efficient, real time relative localisation. This paper explores different data inputs for vision based relative localisation. It introduces a novel dataset generated in \textit{Blender}, providing ground truth optic flow and depth. Comparisons to \textit{MPI Sintel}, an industry/research standard optic flow dataset, show it to be a challenging and realistic dataset. Two Deep Neural Network (DNN) architectures (YOLOv3 & U-Net) were trained on this data, comparing optic flow to colour images for relative positioning. The results indicate that using optic flow provides a significant advantage in relative localisation. The flow based YOLOv3 had an mAP of 48%, 9% better than the RGB based YOLOv3, and 23% better than its equivalent U-Net. Its IoU_{0.5} of 63% was also 14% better than the RGB based YOLOv3, and 51% than its equivalent U-Net. As an input, it generalises better than RGB, as test clips with variant drones show. For these variants, the optical flow based networks outperformed the RGB based networks by a factor of 10.},

note = {de Croon, G.C.H.E. (mentor); de Wagter, C. (graduation committee); Zarouchas, D. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:4e100997-a5b3-4863-a312-4721296fcdba,

title = {Towards landing a deep-stalled flying-wing in a powered flat spin: a proof of concept},

author = {Matteo Barbera},

url = {http://resolver.tudelft.nl/uuid:4e100997-a5b3-4863-a312-4721296fcdba},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Flying-wings show great potential for a vast number of applications, in both commercial and military sectors, thanks to their long range and fast forward flight, but suffer due to their lack of vertical take-off and landing capabilities. This paper presents a proof of concept for a novel landing method for a conventional flying wing that does not introduce additional weight dedicated only to the landing phase, with the aim of controlling a deep-stalled flying-wing in a powered flat spin. Through cyclic actuation of the servo motors and elevons, lateral forces as well as moments can be generated to control the position and attitude of the rotation plane. A successful indoor experiment was performed with a modified Parrot Disco in a controlled environment. Outdoor tests, however, failed to replicate the indoor results due to additional challenges present in the real flight conditions. A number of key challenges were identified, and the insights gained in this research lay an initial foundation for future work on this topic.},

note = {de Wagter, C. (mentor); Remes, B.D.W. (graduation committee); Delft University of Technology (degree granting institution)},

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pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:1136170f-3c4b-43b8-8b43-09e1e52d3bfd,

title = {Cooperative Relative Localization in MAV Swarms with Ultra-wideband Ranging},

author = {Changrui Liu},

url = {http://resolver.tudelft.nl/uuid:1136170f-3c4b-43b8-8b43-09e1e52d3bfd},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Relative localization (RL) is essential for the successful operation of micro air vehicle (MAV) swarms. Achieving accurate 3-D RL in infrastructure-free and GPS-denied environments with only distance information is a challenging problem that has not been satisfactorily solved. In this work, based on the range-based peer-to-peer RL using the ultra-wideband (UWB) ranging technique, we develop a novel UWB-based cooperative relative localization (CRL) solution which integrates the relative motion dynamics of each host-neighbor pair to build a unified dynamic model and takes the distances between the neighbors as bonus information. Observability analysis using differential geometry shows that the proposed CRL scheme can expand the observable subspace compared to other alternatives using only direct distances between the host agent and its neighbors. In addition, we apply the kernel-induced extended Kalman filter (EKF) to the CRL state estimation problem with the novel-designed Logarithmic-Versoria (LV) kernel to tackle heavy-tailed UWB noise. Sufficient conditions for the convergence of the fixed-point iteration involved in the estimation algorithm are also derived. Comparative Monte Carlo simulations demonstrate that the proposed CRL scheme combined with the LV-kernel EKF significantly improves the estimation accuracy owing to its robustness against both the measurement outliers and incorrect measurement covariance matrix initialization. Moreover, with the LV kernel, the estimation is still satisfactory when performing the fixed-point iteration only once for reduced computational complexity.},

note = {de Croon, G.C.H.E. (mentor); Pfeiffer, S.U. (mentor); Mazo, M. (graduation committee); de Wagter, C. (graduation committee); Delft University of Technology (degree granting institution)},

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pubstate = {published},

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@mastersthesis{uuid:baf5b7df-0e0f-45da-8b70-c7c95ead79b6,

title = {Attitude Control of a Tilt-rotor Tailsitter Micro Air Vehicle Using Incremental Control},

author = {Gervase Lovell-Prescod},

url = {http://resolver.tudelft.nl/uuid:baf5b7df-0e0f-45da-8b70-c7c95ead79b6},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {By combining the ability to hover with a wing for fast and efficient horizontal flight, hybrid unmanned aircraft extend the flight envelope and therefore mission capabilities of unmanned aircraft. However, this comes at a cost: increased complexity control-wise and being more susceptible to wind disturbances. This susceptibility to wind gusts is particularly problematic for tailsitters as during hovering and vertical flight their wing is perpendicular to horizontal wind disturbances, often leading to actuator saturation. This paper presents a novel tailsitter micro air vehicle with two leading edge tilting rotors serving as its only actuators. It is shown that thrust vectoring generates sufficient control moment generation alleviating actuator saturation. Incremental nonlinear dynamic inversion (INDI) is implemented for attitude control and is demonstrated to compensate for unmodeled forces and moments whilst only relying on actuator control effectiveness and knowledge of actuator dynamics.},

note = {Smeur, E.J.J. (mentor); Ma, Z. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:1caff7b3-5c17-4b80-abea-19c629ce6051,

title = {Verification & Validation of Focus of Expansion estimation algorithm employing event-based optic flow},

author = {Stefan Knoops},

url = {http://resolver.tudelft.nl/uuid:1caff7b3-5c17-4b80-abea-19c629ce6051},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Event based vision has recently attracted a lot of attention. High data rates and robustness to lighting variations make it a valid option for indoor navigation. The previously developed FAITH algorithm calculates a possible Focus of Expansion
area based on negative half-planes generated by optic flow and by employing a RANSAC search, a fast and reliable Focus of Expansion estimation can be performed. This paper builds upon this algorithm by verifying and validating the
algorithm, improving the derotation capabilities and optimising for computational efficiency. Compared to earlier work, a higher accuracy and an increased robustness are realised by improving the data handling. Simulator results show accuracies in the range of 2 to 5 degrees. Online testing on a drone shows accuracies of up to 5 degrees while obtaining calculation times of only
2 · 10−3s and rates of 140Hz. Comparing the method to an alternative shows higher accuracy and better suitability to normal flow. Further research may contribute to more stable results and explore different hardware solutions.},

note = {de Croon, G.C.H.E. (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:574db806-6096-4600-9926-3d737d1ee7da,

title = {NanoFlowNet: Real-time optical flow estimation on a nano quadcopter},

author = {Rik Bouwmeester},

url = {http://resolver.tudelft.nl/uuid:574db806-6096-4600-9926-3d737d1ee7da},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Nano quadcopters are small, agile, and cheap platforms well suited for deployment in narrow, cluttered environments. Due to their limited payload, nano quadcopters are highly constrained in processing power, rendering conventional vision-based methods for autonomous navigation incompatible. Recent machine learning developments promise high-performance perception at low latency, while novel ultra-low power microcontrollers augment the visual processing power of nano quadcopters. In this work, we present NanoFlowNet, an optical flow CNN that, based on the semantic segmentation architecture STDC-Seg, achieves real-time dense optical flow estimation on edge hardware. We use motion boundary ground truth to guide the learning of optical flow, improving performance with zero impact on latency. Validation on MPI-Sintel shows the high performance of the proposed method given its constrained architecture. We implement the CNN on the ultra-low power GAP8 microcontroller and demonstrate it in an obstacle avoidance application on a 34 g Bitcraze Crazyflie nano quadcopter.},

note = {de Croon, G.C.H.E. (mentor); Paredes-Vallés, Federico (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:4e4e333d-643f-43b9-99cb-650d697f5baa,

title = {ADAPT: A 3 Degrees of Freedom Reconfigurable Force Balanced Parallel Manipulator for Aerial Applications},

author = {KARTIK SURYAVANSHI},

url = {http://resolver.tudelft.nl/uuid:4e4e333d-643f-43b9-99cb-650d697f5baa},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Mechanical, Maritime and Materials Engineering},

abstract = {In this work, we present the ADAPT, a novel reconfigurable force-balanced parallel manipulator with pantograph legs for spatial motions applied underneath a drone. The reconfigurable aspect allows different motion-based 3-DoF operation modes like translational, rotational, mixed, planar without disassembly. For the purpose of this study, the manipulator is used in translation mode only. A kinematic model is developed and validated for the manipulator. The design and motion capabilities are also validated both by conducting dynamics simulations of a simplified model on MSC ADAMS, and experiments on the physical setup.
The force-balanced nature of this novel design decouples the motion of the manipulator’s end-effector from the base, zeroing the reaction forces, making this design ideally suited for aerial manipulation in unmanned aerial vehicles (UAVs) applications, or generic floating-base applications.},

note = {van der Wijk, V. (mentor); Hamaza, S. (graduation committee); Herder, J.L. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:66c34a84-5b47-49dd-b560-2836d9696e3c,

title = {Incremental Nonlinear Dynamic Inversion controller - structural vibration coupling: Study of the phenomenon and the existing solutions},

author = {Alessandro Collicelli},

url = {http://resolver.tudelft.nl/uuid:66c34a84-5b47-49dd-b560-2836d9696e3c},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {Incremental Nonlinear Dynamics Inversion (INDI) flight controllers are sensor-based control systems, that are robust towards model uncertainty and with good disturbance rejection characteristics. These controllers show coupling effects in structural modes when implemented in specific flying vehicles with low-frequency structural motions. This paper investigates different INDI implementations, standard INDI, hybrid INDI, and notch filter placement in the INDI loop via simulation and flight tests on the Nederdrone. System identification of the structural characteristics of the vehicle and the system’s yaw dynamics are executed via ground vibration and hover flight tests. Closed-loop behaviour of theINDI inner-loop, disturbance rejection performance, and outer loop step-tracking performance was assessed with dedicated flight tests. The investigated INDI solutions show similar disturbance rejection and outer-loop step tracking performance, while the hybrid INDI solution performs a better nonlinear dynamic inversion. 
Index Terms—INDI, complementary filter, unmanned vehicle, flight control system structural motion coupling},

note = {Smeur, E.J.J. (mentor); Pollack, T.S.C. (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:6215dd57-8d16-466b-a286-341538675d2d,

title = {A Bio-inspired Sensing Approach to in-Gust Flight of Flapping Wing MAVs},

author = {Chenyao Wang},

url = {http://resolver.tudelft.nl/uuid:6215dd57-8d16-466b-a286-341538675d2d},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering; TU Delft Control & Simulation},

abstract = {Flapping wing micro aerial vehicles (FWMAVs) are known for their flight agility and maneuverability. However, their in-gust flight performance and stability is still inferior to their biological counterparts. To this end, a simplified in-gust dynamic model, which could capture the main gust effects on FWMAVs, has been identified with real in-gust flights' data of a FWMAV, the Flapper Drone. Based on this model, an adaptive position and velocity controller was proposed with gain scheduling and implemented for in-gust flights under gust speeds up to 2.4 m/s. With this airflow-sensing based adaptive controller, the in-gust hovering stability of the Flapper Drone has been improved when the gust's intensity and frequency changes, comparing with the original fixed-gain cascaded PID controller case.},

note = {Hamaza, S. (mentor); de Croon, G.C.H.E. (mentor); Wang, S. (graduation committee); de Wagter, C. (graduation committee); van Oudheusden, B.W. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

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@mastersthesis{uuid:05f743a5-39c8-4860-9976-1eee532184a9,

title = {Developing a modular tool to simulate regeneration power potential using orographic wind-hovering UAVs},

author = {Midas Gossye},

url = {http://resolver.tudelft.nl/uuid:05f743a5-39c8-4860-9976-1eee532184a9},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {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.},

note = {Remes, B.D.W. (mentor); Hwang, S. (graduation committee); de Croon, G.C.H.E. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:41222049-fb57-4f26-9b9e-85939af9fa63,

title = {Sensorless Impedance Control for Curved Surface Inspections Using the Omni-Drone Aerial Manipulator},

author = {Hani Abu-Jurji},

url = {http://resolver.tudelft.nl/uuid:41222049-fb57-4f26-9b9e-85939af9fa63},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {In this thesis, we develop a novel aerial manipulator system with an omni-directional workspace. The system comprises of a quadrotor platform equipped with a rotating five-bar linkage and serves the purpose of demonstrating the ability to perform contour tracing tasks on complex shapes, whilst airborne. In order to remove the dependency on additional force sensors and keep the design lightweight, an onboard force estimation scheme is implemented based on the generalized momentum of the system, using the torque feedback from the manipulator's motors. The computed force estimate feeds in a position-based impedance controller with the purpose of maintaining continuous contact through the manipulator's end-effector as the system traces contours of unknown curved geometry. Results demonstrate the estimator's ability to track the applied forces, while the impedance controller shows adequate contour following. The preliminary results obtained on both stationery and flight experiments validate this approach and show potential for aerial contact inspections of more complex structures.},

note = {Hamaza, S. (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:df815057-9ab6-42ee-8290-ce8099ffda68,

title = {Incremental Nonlinear Dynamic Inversion Controller for a Variable Skew Quad Plane},

author = {Tomaso De Ponti},

url = {http://resolver.tudelft.nl/uuid:df815057-9ab6-42ee-8290-ce8099ffda68},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {This paper presents the design of an Incremental Nonlinear Dynamic Inversion (INDI) controller for the novel platform VSQP. Part of the identified challenges is the develop- ment of a model for the actuator effectiveness and lift especially as a function of skew, the newly added degree of freedom. In particular it is assumed that the actuator effectiveness changes linearly with actuator state and that aerodynamic forces change quadratically with airspeed and depend mainly on the chordwise component of airspeed. Moreover, the position of the moving actuators is expressed as a function of the corresponding moment arm and the skew angle. The models and assumptions are verified through static and dynamic wind tunnel tests at the OJF of TuDelft. A WLS routine is used to solve the control allocation for the overactuated guidance loop. A lower cost is assigned to the use of the push motor so to steer the control allocation in its favor rather than commanding changes in attitude. A gradual switch of the hover motors in transition is achieved by scheduling the lift-pitch effectiveness with airspeed. Therefore, as airspeed increases the outerloop INDI controller evaluates that changing pitch to achieve a certain vertical acceleration set point results in an increasingly cheaper command allocation than changing thrust. An automatic skew controller is designed based on the developed control moment and lift models. The skew angle is scheduled with airspeed so to perform transition while also maximizing control authority. Finally, the controller is validated by performing multiple transitions inside the OJF windtunnel.},

note = {Smeur, E.J.J. (mentor); Remes, B.D.W. (graduation committee); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:fdd8e2fa-1372-4f79-aa05-6ab152e848e1,

title = {Adaptive control with Multivariate B-Splines and INDI: A case study for Vertical take-off and landing drones},

author = {Prawien Kanhai},

url = {http://resolver.tudelft.nl/uuid:fdd8e2fa-1372-4f79-aa05-6ab152e848e1},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {In recent years the popularity of VTOL (Vertical Take-Off and Landing) drones has increased significantly. Due to their hybrid design, these drones can take off and land vertically and fly horizontally, enabling them to land in difficult terrain and have a more extensive range than the Quadcopter counterpart. However, this hybrid design also introduces complex dynamics that are difficult to model. For adequate control, this requires an adaptive element that can compensate for the modeling errors. Due to the significant change in flight conditions, adaptations must be made effectively over the entire flight envelope of a VTOL drone. This thesis introduces an adaptive controller that can cope with the large flight envelope and varying flight conditions of the VTOL drone and can adapt the controller effectively and store previous adaptations with multivariate B-splines during real-time flights.},

note = {Smeur, E.J.J. (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}

@mastersthesis{uuid:b7070c31-9db1-4a0c-8605-fb871914501b,

title = {UWB Localisation: Distributed UWB inter-ranging for MAV swarms in large GNSS-denied environments},

author = {Fréderic Dupon},

url = {http://resolver.tudelft.nl/uuid:b7070c31-9db1-4a0c-8605-fb871914501b},

year  = {2022},

date = {2022-01-01},

school = {TU Delft Aerospace Engineering},

abstract = {The use of micro air vehicles (MAV) is becoming increasingly mainstream and with them their applications have become more demanding across the board. The application of MAV’s in large GNSS-denied environments often asks for a distributed and scalable localisation system with minimal reliance on static localisation hardware. In this research a distributed ultra-wideband (UWB) localisation system that takes advantage of the collaborative capabilities of a swarm of MAV’s has been developed and tested in both simulation and practice. Additionally, a modular UWB simulator has been developed which enables researchers to test UWB localisation schemes for a swarm of MAV’s. It has been found that when taking advantage of the UWB inter-agent ranging capabilities of a swarm of micro air vehicles, one can increase the coverage of an UWB setup in spaces with coverage-issues and conversely increase the accuracy of an existing UWB setup that has full UWB coverage.},

note = {de Croon, G.C.H.E. (mentor); Pfeiffer, S.U. (mentor); Delft University of Technology (degree granting institution)},

keywords = {},

pubstate = {published},

tppubtype = {mastersthesis}

}