Intelligently Assisting Human-Guided Quadcopter Photography
This work addresses safety and efficiency issues for amateur and professional drone photographers, though it is incremental as it builds on existing semi-autonomous methods.
The paper tackled the problem of inexperienced drone pilots causing collisions and poor photo framing by developing an intelligent user interface that retains human control while improving navigation and photo quality, resulting in reduced crashes and positive user feedback.
Drones are a versatile platform for both amateur and professional photographers, enabling them to capture photos that are impossible to shoot with ground-based cameras. However, when guided by inexperienced pilots, they have a high incidence of collisions, crashes, and poorly framed photographs. This paper presents an intelligent user interface for photographing objects that is robust against navigation errors and reliably collects high quality photographs. By retaining the human in the loop, our system is faster and more selective than purely autonomous UAVs that employ simple coverage algorithms. The intelligent user interface operates in multiple modes, allowing the user to either directly control the quadcopter or fly in a semi-autonomous mode around a target object in the environment. To evaluate the interface, users completed a data set collection task in which they were asked to photograph objects from multiple views. Our sketchbased control paradigm facilitated task completion, reduced crashes, and was favorably reviewed by the participants.