Searched for: subject:"Quadcopter"
(1 - 13 of 13)
document
Solanki, Prashant (author)
Quadcopters are becoming increasingly popular across diverse sectors such as mapping, photography, or surveillance. Since rotor damages occur frequently, it is essential to improve the attitude estimation and thus ultimately the ability to control a damaged quadcopter. The Control and Simulation group of TU Delft developed a quadcopter...
master thesis 2020
document
Koomen, Lenard (author)
The combination of reinforcement learning and deep neural networks has the potential to train intelligent autonomous agents on high dimensional sensory inputs, with applications in flight control. However, the amount of samples needed by these methods is often too large to use real-world interaction. In this work, mirror-descent guided policy...
master thesis 2020
document
Koning, Tim (author)
Reinforcement Learning (RL) is a learning paradigm where an agent learns a task by trial and error. The agent needs to explore its environment and by simultaneously receiving rewards it learns what is appropriate behaviour.<br/>Even though it has roots in machine learning, RL is essentially different from other machine learning methods. In...
master thesis 2020
document
Fris, Rein (author)
Deep Reinforcement Learning (DRL) enables us to design controllers for complex tasks with a deep learning approach. It allows us to design controllers that are otherwise cumbersome to design with conventional control methodologies. Often, an objective for RL is binary in nature. However, exploring in environments with sparse rewards is a problem...
master thesis 2020
document
Ledzian, Patrick (author)
Decentralized control and estimation are both active research areas in the field of systems and control. A new approach to these topics utilizes graph theory to characterize inter-agent communication as a graph that, in this thesis, can have time-varying topology. This approach has been named "network-decentralized" and the use of network...
master thesis 2019
document
van Dam, Geart (author)
This research investigates and proposes a new method for obstacle detection and avoidance on quadrotors. One that does not require the addition of any sensors, but relies solely on measurements from the accelerometer and rotor controllers. The detection of obstacles is based on the principle that the airflow around a quadrotor changes when the...
master thesis 2019
document
van Vrede, Daan (author)
Both quadcopter Micro Aerial Vehicles (MAVs) and Flapping Wing MAVs (FWMAVs) are constrained in Size, Weight and Processing power (SWaP) in order to achieve flight tasks that include attitude and velocity stabilisation, as well as obstacle avoidance. <br/>Conventional sensory and control approaches, such as those relying on inertial, visual and...
master thesis 2018
document
Braber, T.I. (author)
On-board stabilization of quadrotors is often done using an Inertial Measurement Unit (IMU), aided by additional sensors to combat the IMU drift. For example, GPS readings can aid when flying outdoors, or when flying in GPS denied environments, such as indoors, visual information from one or more camera modules can be used. <br/>A single...
master thesis 2017
document
Naruta, Anton (author)
This paper describes an implementation of a reinforcement learning-based framework applied to the control of a multi-copter rotorcraft. The controller is based on continuous state and action Q-learning. The policy is stored using a radial basis function neural network. Distance-based neuron activation is used to optimize the generalization...
master thesis 2017
document
Vicente Melo E Carvalho Marques, Mariana (author)
L1 adaptive control is a relatively new technique that attempts to tackle the robustness shortcoming of the MRAC controller by applying a low pass filter to the control input. It can be used as an augmentation loop using baseline controllers such as backstepping or PID. This controller has been implemented as an augmentation loop with both these...
master thesis 2017
document
Abuter Grebe, Nicolás Omar (author)
State of the art trajectory generation schemes for quadrotors assume a simple dynamic model.<br/>They neglect aerodynamic effects such as induced drag and blade flapping and assume that no<br/>wind is present. In order to overcome this limitation, this thesis investigates a trajectory optimization scheme based upon Differential Dynamic...
master thesis 2017
document
Höppener, D.C. (author)
Incremental Nonlinear Dynamic Inversion provides a high performance attitude controller for multi-rotor Micro Aerial Vehicles by providing very good disturbance rejection capabilities. Flights conducted with a quadcopter revealed undesired pitch and rolling motions which occurred simultaneously with actuator saturation for instantaneous yaw...
master thesis 2016
document
Molenkamp, D. (author)
A novel intelligent controller selection method for quadrotor attitude and altitude control is presented that maintains performance in different regimes of the flight envelope. Conventional quadrotor controllers can behave insufficiently during aggressive manoeuvring, in extreme angles the quadrotor is unable to maintain height which may result...
master thesis 2016
Searched for: subject:"Quadcopter"
(1 - 13 of 13)