A comparison of adaptive view techniques for exploratory 3D drone teleoperation

John Thomason, Photchara Ratsamee, Jason Orlosky, Kiyoshi Kiyokawa, Tomohiro Mashita, Yuki Uranishi, Haruo Takemura

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Drone navigation in complex environments posesmany problems to teleoperators. Especially in three dimensional (3D) structures such as buildings or tunnels, viewpoints are often limited to the drone's current camera view, nearby objects can be collision hazards, and frequent occlusion can hinder accurate manipulation. To address these issues, we have developed a novel interface for teleoperation that provides a user with environment-adaptive viewpoints that are automatically configured to improve safety and provide smooth operation. This real-time adaptive viewpoint system takes robot position, orientation, and 3D point-cloud information into account to modify the user's viewpoint to maximize visibility. Our prototype uses simultaneous localization and mapping (SLAM) based reconstruction with an omnidirectional camera, and we use the resulting models as well as simulations in a series of preliminary experiments testing navigation of various structures. Results suggest that automatic viewpoint generation can outperform first- and third-person view interfaces for virtual teleoperators in terms of ease of control and accuracy of robot operation.

Original languageEnglish (US)
Article number17
JournalACM Transactions on Interactive Intelligent Systems
Issue number2-3
StatePublished - Mar 2019
Externally publishedYes


  • Drone navigation
  • View management

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Artificial Intelligence


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