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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Robot. AI | doi: 10.3389/frobt.2019.00095

High-Level Teleoperation System For Aerial Exploration Of Indoor Environments

  • 1Institute for Computer Graphics and Vision, Graz University of Technology, Austria
  • 2ETH Zürich, Switzerland

Exploration of challenging indoor environments is a demanding task. While automation with aerial robots seems a promising solution, fully autonomous systems still struggle with high-level cognitive tasks and intuitive decision making. To facilitate automation, we introduce a novel teleoperation system with an aerial telerobot that is capable of handling all demanding low-level tasks. Motivated by the typical structure of indoor environments, the system creates an interactive scene topology in real-time that reduces scene details and supports affordances. Thus, difficult high-level tasks can be effectively supervised by a human operator. To elaborate on the effectiveness of our system during a real-world exploration mission, we conducted a user study. Despite being limited by real-world constraints, results indicate that our system better supports operators with indoor exploration, compared to a baseline system with traditional joystick control.

Keywords: telerobotics, System design, Indoor Exploration Tasks, Teleoperation systems, Unmanned Aerial Vehicles - UAV, Scene abstraction

Received: 01 Mar 2019; Accepted: 17 Sep 2019.

Copyright: © 2019 Isop, Gebhardt, Nägeli, Fraundorfer, Hilliges and Schmalstieg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mr. Werner A. Isop, Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria, isop@icg.tugraz.at