Exploring Alternative Control Modalities for Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs), commonly known as drones, are defined by the International Civil Aviation Organization (ICAO) as an aircraft without a human pilot on board. They are currently utilized primarily in the defense and security sectors but are moving towards the general market in surprisingly powerful and inexpensive forms. While drones are presently restricted to non-commercial recreational use in the USA, it is expected that they will soon be widely adopted for both commercial and consumer use. Potentially, UAVs can revolutionize various business sectors including private security, agricultural practices, product transport and maybe even aerial advertising. Business Insider foresees that 12% of the expected $98 billion cumulative global spending on aerial drones through the following decade will be for business purposes.[28] At the moment, most drones are controlled by some sort of classic joystick or multitouch remote controller. While drone manufactures have improved the overall controllability of their products, most drones shipped today are still quite challenging for inexperienced users to pilot. In order to help mitigate the controllability challenges and flatten the learning curve, gesture controls can be utilized to improve piloting UAVs. The purpose of this study was to develop and evaluate an improved and more intuitive method of flying UAVs by supporting the use of hand gestures, and other non-traditional control modalities. The goal was to employ and test an end-to-end UAV system that provides an easy-to-use control interface for novice drone users. The expectation was that by implementing gesture-based navigation, the novice user will have an overall enjoyable and safe experience quickly learning how to navigate a drone with ease, and avoid losing or damaging the vehicle while they are on the initial learning curve. During the course of this study we have learned that while this approach does offer lots of promise, there are a number of technical challenges that make this problem much more challenging than anticipated. This thesis details our approach to the problem, analyzes the user data we collected, and summarizes the lessons learned