Abstract
Unmanned aerial vehicles (UAVs) have increasingly attracted great attention in remote sensing for 3D aerial mappings over the past decade. UAVs are feasible to fly through a target sensing area with little or no human intervention in the practical fieldworks. In addition, UAVs can travel across hazardous, dangerous, or uninhabited areas, due to their flexibility and long-range flight capacity. However, there are several major challenges in running UAV-enabled sensing missions by casual users. First of all, the current capital price of UAV devices and their correspondingsensors are still expensive. Secondly, it requires professional UAV flight training and
licenses for the remote sensing operation. Third, UAV sensing needs deep technical knowledge and various algorithms for flight trajectory planning, energy consumption, and data gathering.
To address the aforementioned constraints, this thesis proposes a drone-sharing solution and aims to make UAVs accessible for everyone. We establish an on-demand UAV sensing model that connects UAV service providers with potential users. The proposed system works as a service by delivering a sensing request from the UAV service user to the service provider. In particular, the sensing request includes the geometry information of the target areas. In addition, the on-demand system can calculate the flight parameters, total coverage area, and estimated sensing price. The system will also assign the sensing task to a UAV service provider. Once
the user completes the online payment, the flight mission is run by the UAV service provider based on the recommend flight trajectory sent by the system. Finally, the collected dataset are delivered to the users during or after the flight mission. Meanwhile, the calculated operational cost is sent to the UAV provider. The flight mission is then set as completed.
This thesis also proposes a UAV platform that is specifically designed for the on-demand UAV sensing. A detailed UAV platform implementation is introduced, which provides practical system implementation and validation. Moreover, standard operating procedures and setup guidelines are discussed and provided for the on-demand UAV sensing. Last but not least, we propose a user-friendly interface, which illustrates the connections among the internal modules of the system from the user’s perspective.
In summary, this thesis provides a drone-sharing solution to minimize the capital price of UAVs, on-board sensors, and their accessories. Furthermore, it will close the gap between UAV sensing and end-users. With the proposed on-demand UAV sensing, casual users are able to collect quality videos or images from their target areas without preliminary aviation or aerodynamic knowledge.
| Date of Award | 2021 |
|---|---|
| Original language | English |
| Supervisor | Mohammad ABUALSHEIKH (Supervisor), Roland Goecke (Supervisor) & Damith HERATH (Supervisor) |