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Thesis project proposals
Control of a drone with faulty motors
In this project we study the control of a drone when one or more motors have failed. This would typically result in the drone crashing. However, it has been shown that the drone can stay in the air even when such failures occur and that the platform can detect such failures automatically. This project is about investigate this problem with the aim to come up with an algorithm that would allow a drone to handle a failure gracefully.
Literature
Required skills: Solid knowledge of control theory and systems modelling, programming,
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
Semantic labeling and object recognition from a drone
In this project the aim is to investigate methods for semantically labelling indoor scenes using drone and to recognise objects in those scenes. The scenario is a drone that moves around in an indoor environment in need of renovation. The algorithms developed in this thesis has the aim of identifying the type of carpet/floor that is on the ground and what appliances are in an apartment.
Required skills: Computer vision, machine learning, programming
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
Ego motion estimation on a drone using visual intertial sensors
One of the key components in a drone system is the ability to estimate the position. In this project we investigate methods for ego motion estimation with the am to generate a position estimate that is robust and accurate for periods on the orders of tens of seconds.
Literature
- ICRA 2016 tutorial slides
- D. Scaramuzza and F. Fraundorfer, "Visual Odometry [Tutorial]: Part I - The First 30 Years and Fundamentals", IEEE Robotics and Automation Magazine, Volume 18, issue 4, 2011
- F. Fraundorfer and D. Scaramuzza, "Visual odometry: Part II - Matching, robustness, optimization, and applications", IEEE Robotics and Automation Magazine, Volume 19, issue 2, 2012
- C. Forster, M. Pizzoli, and D. Scaramuzza, "SVO: Fast Semi-Direct Monocular Visual Odometry", IEEE International Conference on Robotics and Automation, Hong Kong, China, May 2014
- C. Forster, L. Carlone, F. Dellaert, and D. Scaramuzza, "On-Manifold Preintegration for Real-Time Visual-Inertial Odometry", IEEE Transactions on Robotics, to appear, 2016
- M. Faessler, F. Fontana, C. Forster, E. Mueggler, M. Pizzoli, and D. Scaramuzza, "Autonomous, Vision-based Flight and Live Dense 3D Mapping with a Quadrotor Micro Aerial Vehicle", Journal of Field Robotics, 2015
Required skills: Solid knowledge of control theory and systems modelling, programming,
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
User interface for a teleoperated drone
Required skills: ROS, programming,
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
Safe navigation with a drone in office environments
Required skills: ROS, programming,
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
Autonomous exploration with a drone
Required skills: ROS, programming
Resources: KTH CAS will supply a drone to work with
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
UWB positioning of drones
In this project we study ultra wideband (UWB) as a means for positioning of a drone. Examples in the literature show that it should be possible to use UWB combined with information from an IMU to position the drone well enough to control its flight. In this project we will study the use of different setups of the UWB system, to generate, for example, ToA or TDoA measurements. The study should consider i) scalability (can it be used for many drones or just one?), ii) update rate (how often can we get data?), iii) accuracy (how accurate are the measurements?), iv) reliability (how reliable is the signal that we get? are there man outliers?). If and in what situations an IMU is needed should also be investigated. The output of the project is expected to be one or several algorithms for positioning using UWB.
Literature
Required skills: Programming, Kalman filtering and similar, control theory
External collaboration: The project will be conducted in collaboration with the company Loligo which will be responsible for the UWB hardware.
Resources: KTH CAS will supply a drone to work with and Loligo will provide the UWB hardware
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.
Automatic recharging of drones for extended periods of operation
One of the common denominators of battery powered drones is that they can only operate for short periods of time, typically 10-15 and very rarely above 30min. Many applications would require longer periods of operation. Today the common way to handle this is to manually change the battery. To realise a fully autonomous system, a drone needs to be able to automatically recharge the batteries. This would then also cater for longer periods of operations, albeit with pauses for recharging. The aim the project is to came up with a safe and cost effective solution for autonomous charging of drones. There are several problems associated with this.The drone needs to be able to position itself with respect to the charging station. It needs to be able to land in such that charging can happen. A method for charging the drone in safe and efficient way is needed. The drone should ideally be able to calculate when t needs to return to the recharging station so that it reaches it without running out of battery power. The focus of the master thesis project will be on the first and second of these aspects, with some thoughts going into the fourth issue.
Required skills: Programming, control theory
External collaboration: The project will be conducted in collaboration with the company Loligo which will be responsible for the recharging solution and hardware.
Resources: KTH CAS will supply a drone to work with and Loligo will supply the recharging hardware.
Where to work: It is foreseen that the majority of the time will be spent at KTH CAS.