Paper Info
Title
Flycam: Multitouch Gesture Controlled Drone Gimbal Photography
Abstract
We introduce FlyCam-a novel framework-for gimbal drone camera photography. Our approach abstracts the camera and the drone into a single flying camera object so that the user does not need to think about the drone movement and camera control as two separate actions. The camera is controlled from a single mobile device with six simple touch gestures such as rotate, move forward, yaw, and pitch. The gestures are implemented as seamless commands that combine the gimbal motion with the drone movement. Moreover, we add a sigmoidal motion response that compensates for abrupt drone swinging when moving horizontally. The smooth and simple camera movement has been evaluated by user study, where we asked 20 human subjects to mimic a photograph taken from a certain location. The users used both the default two joystick control and our new touch commands. Our results show that the new interaction performed better in both intuitiveness and easiness of navigation. The users spent less time on task, and the System Usability Scale index of our FlyCam method was 75.13, which is higher than the traditional dual joystick method that scored at 67.38. Moreover, the NASA task load index also showed that our method had lower workload than the traditional method.
Year
DOI
Venue
2018
10.1109/LRA.2018.2856271
IEEE ROBOTICS AND AUTOMATION LETTERS
Keywords
Field
DocType
Gesture, posture and facial expressions, teler-obotics and teleoperation, virtual reality and interfaces
Computer vision,Task analysis,Gesture,Control engineering,Photography,Mobile device,Artificial intelligence,Drone,Engineering,Joystick,System usability scale,Gimbal
Journal
Volume
Issue
ISSN
3
4
2377-3766
Citations 
PageRank 
References 
1
0.37
0
Authors
5
Name
Order
Citations
PageRank
Hao Kang191.84
Haoxiang Li221010.94
Jianming Zhang385335.35
Xin Lu458627.15
Bedrich Benes5127680.15