Examining Distance in UAV Gesture Perception

Karissa Jelonek, Paul Fletcher, Brittany Duncan, Carrick Detweiler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Unmanned aerial vehicles (UAVs) are becoming more common, presenting the need for effective human-robot communication strategies that address the unique nature of unmanned aerial flight. Visual communication via drone flight paths, also called gestures, may prove to be an ideal method. However, the effectiveness of visual communication techniques is dependent on several factors including an observer's position relative to a UAV. Previous work has studied the maximum line-of-sight at which observers can identify a small UAV [1]. However, this work did not consider how changes in distance may affect an observer's ability to perceive the shape of a UAV's motion. In this study, we conduct a series of online surveys to evaluate how changes in line-of-sight distance and gesture size affect observers' ability to identify and distinguish between UAV gestures. We first examine observers' ability to accurately identify gestures when adjusting a gesture's size relative to the size of a UAV. We then measure how observers' ability to identify gestures changes with respect to varying line-of-sight distances. Lastly, we consider how altering the size of a UAV gesture may improve an observer's ability to identify drone gestures from varying distances. Our results show that increasing the gesture size across varying UAV to gesture ratios did not have a significant effect on participant response accuracy. We found that between 17 m and 75 m from the observer, their ability to accurately identify a drone gesture was inversely proportional to the distance between the observer and the drone. Finally, we found that maintaining a gesture's apparent size improves participant response accuracy over changing line-of-sight distances.

Original languageEnglish (US)
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages879-885
Number of pages7
ISBN (Electronic)9781665479271
DOIs
StatePublished - 2022
Event2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 - Kyoto, Japan
Duration: Oct 23 2022Oct 27 2022

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2022-October
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
Country/TerritoryJapan
CityKyoto
Period10/23/2210/27/22

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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