Modular Neural Network Navigation for Autonomous Nano Drone Racing

In this study, we present a first step towards a cutting-edge software framework that will enable autonomous racing capabilities for nano drones. Through the integration of neural networks tailored for real-time operation on resource-constrained devices. A lightweight Convolutional Neural Network, with the Gatenet architecture, is adjusted for...

An Adaptive Neural Network Quadrotor Trajectory Tracking Controller Tolerant to Propeller Damage

Executing quadrotor trajectories accurately and therefore safely is a challenging task. State-of-the-art adaptive controllers achieve impressive trajectory tracking results with slight performance degradation in varying winds or payloads, but at the cost of computational...

Guidance & Control Networks for Time-Optimal Quadcopter Flight

Reaching fast and autonomous flight requires computationally efficient and robust algorithms. To this end, we train Guidance & Control Networks to approximate optimal control policies ranging from energy-optimal to time-optimal flight. We show that the policies become more difficult to learn the closer we get to the time-optimal ’bang-bang’...

Stability control and positional water jet placement for a novel tethered unmanned hydro-propelled aerial vehicle using real-time water jet detection

Aerial platforms designed for water jet placement are gaining interest in the areas of fire-fighting, washing, and irrigation. A novel, lightweight, and simplistic design is proposed that reduces the number of actuators and limits ineffective water discharge. External camera feedback was used for position control as a first step towards...

Towards landing a deep-stalled flying-wing in a powered flat spin: a proof of concept

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...

An Adaptive Control Strategy for Neural Network based Optimal Quadcopter Controllers

Developing optimal controllers for aggressive high speed quadcopter flight remains a major challenge in the field of robotics. Recent work has shown that neural networks trained with supervised learning are a good candidate for real-time optimal quadcopter control. In these methods, the networks (termed G\&CNets) are trained using optimal...

High-Dimensional Optimal State-Feedback Mapping using Deep Neural Networks for Agile Quadrotor Flight

For most robotics applications, optimal control remains a promising solution for solving complex control tasks. One example is the time-optimal flight of Micro Air Vehicles (MAVs), where strict computational requirements fail to resolve such algorithms onboard. Recent work on the use of deep neural networks for guidance and control (G&CNets)...

Improving the Performance of INDI Flight Control for a Quadrotor in the Ceiling Effect

As the application areas of Unmanned Aerial Vehicles (UAVs) keep expanding, new flight areas are encountered more often. Small UAVs, named Micro Air Vehicles (MAVs), even fly in areas like sewage pipes. These areas introduce new difficulties such as aerodynamic effects caused by the ground and/or ceiling. In this paper two main contributions are...

Hybrid UAV Attitude Control using INDI and Dynamic Tilt-Twist

The application of Unmanned Aerial Vehicles (UAVs) is increasing, much like the performance of these aircraft. A tailsitter is a type of UAV which is capable of performing vertical take-offs and landings (VTOL) and long endurance flights. During hover, the yaw control is limited due to the dynamics of these tailsitters. The generally used...

Extended Incremental Non-linear Control Allocation on the TU Delft Quadplane

This research presents an implementation of a novel controller design on an overactuated hybrid Unmanned Aerial Vehicle (UAV). This platform is a hybrid between a conventional quadcopter and a fixed-wing aircraft. Its inner loop is controlled by an existing but modified control method called Incremental Non-linear Control Allocation or INCA....

Attitude modeling of the DelftaCopter: a system identification approach

Previous years have seen a rise in the use of Unmanned Aerial Vehicles (UAVs). Reaching a large endurance and range while being able to perform Vertical Take-Off and Landing (VTOL) landings allows a broad range of applications. For this purpose the DelftaCopter (DC) was developed, a tilt-body tailsitter UAV. It hovers using a single helicopter...

Hear-and-avoid for UAVs using convolutional neural networks

We investigate how an Unmanned Air Vehicle (UAV) can detect manned aircraft with a single microphone. In particular, we create an audio data set in which UAV ego-sound and recorded aircraft sound can be mixed together, and apply convolutional neural networks to the task of air traffic detection. Due to restrictions on flying UAVs close to...

Differential Dynamic Programming for Aerial Robots using an Aerodynamics Model

State of the art trajectory generation schemes for quadrotors assume a simple dynamic model. They neglect aerodynamic effects such as induced drag and blade flapping and assume that no wind is present. In order to overcome this limitation, this thesis investigates a trajectory optimization scheme based upon Differential Dynamic Programming (DDP)...

The influence of a bottom camera in indoor ground-segmentation based obstacle avoiding performance for MAVs

Actuator Saturation Handling using Weighted Optimal Control Allocation Applied to an INDI Controlled Quadcopter

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...

Tracking and Following a Moving Person Onboard a Small Pocket Drone

This paper presents a vision based strategy, designed to work fully onboard a small pocket drone, for autonomously tracking and following a person. Flying a drone is not an easy task, usually requiring a trained pilot, with the presented system it is possible to use a drone for filming or taking pictures from previously inaccessible places...

Fixed-Wing UAV Integrated Navigation with Low-Cost IMU/GPS

Today, there is an increase in the use of Unmanned Aerial Vehicles (UAV's), for applications that can be considered dull, dirty or dangerous when compared to those applications of conventional aircraft or helicopters. To further increase the use of UAV's, their navigation filters must be robust and reliable. The trend in current autopilot...

Optical Flow Based State Estimation for an Indoor Micro Aerial Vehicle

This work addresses the problem of indoor state estimation for autonomous flying vehicles with an optic flow approach. The paper discusses a sensor configuration using six optic flow sensors of the computer mouse type augmented by a three-axis accelerometer to estimate velocity, rotation, attitude and viewing distances. It is shown that the...