Intelligently Assisting Human-Guided Quadcopter Photography
Abstract
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 sketch-based control paradigm facilitated task completion, reduced crashes, and was favorably reviewed by the participants.
Publication Date
1-1-2018
Publication Title
Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018
Number of Pages
336-341
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
85071457418 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85071457418
STARS Citation
Alabachi, Saif and Sukthankar, Gita, "Intelligently Assisting Human-Guided Quadcopter Photography" (2018). Scopus Export 2015-2019. 10036.
https://stars.library.ucf.edu/scopus2015/10036