Abstract
Interaction between humans and unmanned aerial vehicles is a promising field for future applications. However, current interfacing paradigms either imply the presence of intermediary hardware as monitors, joysticks and haptic devices, or are limited to visual/auditory channels with hand gestures, voice recognition, or interpretation of face poses and body postures. Another paradigm, physical human–robot interaction, which is based on mutual exchange of forces, is popular when dealing with robotic arms and humanoids, while unmanned aerial vehicles are usually considered too dangerous and lack proper interaction surfaces to exchange forces. In this paper, we address the problem of physical human–unmanned aerial vehicle interaction and we propose a straightforward approach to allow a human to intuitively command an unmanned aerial vehicle through exchanges of forces. Using a residual based estimator, we estimate the external forces and torques acting on the unmanned aerial vehicle. Through the employment of a sensor ring, we are able to separate the human interaction forces from additional disturbances as wind and parameter uncertainties. This knowledge is used inside a control framework where the human is allowed to change the desired trajectory by simply applying forces on the unmanned aerial vehicle. The system is validated with multiple hardware-in-the-loop simulations and experiments in which we try different interaction modalities.
| Original language | English |
|---|---|
| Pages (from-to) | 800-819 |
| Number of pages | 20 |
| Journal | International Journal of Robotics Research |
| Volume | 36 |
| Issue number | 5-7 |
| DOIs | |
| Publication status | Published - 2017 Jun 1 |
Bibliographical note
Funding Information:The authors would like to thank Jannik Romanowski from the mechanical workshop of the Max Planck Institute for Biological Cybernetics, T?bingen, for his effort in the design and the manufacture of the quadrotor hardware. The authors would also like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work of Sujit Rajappa and Paolo Stegagno was supported by PhD and Research Scientist stipends from the Max Planck Society.
Publisher Copyright:
© The Author(s) 2017.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Keywords
- Human–unmanned aerial vehicle interaction
- admittance control
- aerial robot
- force estimator
- nonlinear observer
- unmanned aerial vehicle
ASJC Scopus subject areas
- Software
- Modelling and Simulation
- Mechanical Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering
- Applied Mathematics