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Dynamic Target Tracking and Obstacle Avoidance using a Drone

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Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

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Abstract

This paper focuses on tracking dynamic targets using a low cost, commercially available drone. The approach presented utilizes a computationally simple potential field controller expanded to operate not only on relative positions, but also relative velocities. A brief background on potential field methods is given, and the design and implementation of the proposed controller is presented. Experimental results using an external motion capture system for localization demonstrate the ability of the drone to track a dynamic target in real time as well as avoid obstacles in its way.

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Acknowledgements

The authors would like to specially thank the Motion Analysis Corporation for their support of the Motion Tracking System (MTS) setup at the Advanced Robotics and Automation (ARA) Lab at the University of Nevada, Reno. This project is partially supported by University of Nevada, Reno and NSF-NRI grant number 1426828.

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Authors and Affiliations

  1. Advanced Robotics and Automation Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, NV, 89557, USA

    Alexander C. Woods & Hung M. La

Authors
  1. Alexander C. Woods
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  2. Hung M. La
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Corresponding author

Correspondence to Hung M. La .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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© 2015 Springer International Publishing Switzerland

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Woods, A.C., La, H.M. (2015). Dynamic Target Tracking and Obstacle Avoidance using a Drone. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_76

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  • DOI: https://doi.org/10.1007/978-3-319-27857-5_76

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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