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High-Level Teleoperation System for Aerial Exploration of Indoor Environments.

Werner Alexander Isop1, Christoph Gebhardt2, Tobias Nägeli2

  • 1Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria.

Frontiers in Robotics and AI
|January 27, 2021
PubMed
Summary

This study introduces a novel teleoperation system for aerial robots, enabling human operators to effectively supervise challenging indoor exploration tasks. The system simplifies complex environments, improving control compared to traditional methods.

Keywords:
indoor exploration tasksinteractive scene topologyscene abstractionsearch and rescueteleoperation systemsteleroboticsunmanned aerial vehicles - UAV

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Autonomous Systems

Background:

  • Indoor environment exploration presents significant challenges for fully autonomous aerial robots.
  • Current autonomous systems struggle with high-level cognitive tasks and intuitive decision-making in complex indoor spaces.

Purpose of the Study:

  • To introduce a novel teleoperation system for aerial telerobots designed to handle demanding low-level tasks.
  • To facilitate human supervision of high-level cognitive tasks during indoor exploration.

Main Methods:

  • Development of a teleoperation system with an aerial telerobot capable of managing low-level tasks.
  • Real-time creation of an interactive scene topology that simplifies details and provides affordances.
  • User study comparing the novel system against a traditional joystick control baseline.

Main Results:

  • The developed system effectively supports human operators in supervising high-level tasks.
  • User study results indicate superior operator support for indoor exploration compared to traditional joystick control.
  • The system's interactive scene topology aids in reducing complexity for operators.

Conclusions:

  • The novel teleoperation system enhances human supervision capabilities for aerial robot-assisted indoor exploration.
  • The system's approach to simplifying scene topology and handling low-level tasks improves operator effectiveness.
  • This work offers a promising direction for improving human-robot collaboration in challenging environments.