Autonomous flying with quadrocopter using fuzzy control and ArUco markers | Intelligent Service Robotics Skip to main content
Springer Nature Link
Log in

Autonomous flying with quadrocopter using fuzzy control and ArUco markers

  • Original Research Paper
  • Published:
Intelligent Service Robotics Aims and scope Submit manuscript

Abstract

In this paper, we present an approach which enables a low-cost quadrocopter to fly various trajectories autonomously. Artificial landmarks are used for pose estimation, and a fuzzy controller is utilized to generate steering commands. The presented system can navigate a low-cost quadrocopter along a predefined path without the need for any additional external sensors. In addition to a full description of our system, we also introduce our software package for Robot Operating System, which allows the robotics community to experiment with proposed mapping algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Bry A et al (2015) Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments. The International Journal of Robotics Research. 34(7):969–1002. doi:10.1177/0278364914558129

    Article  Google Scholar 

  2. Hehn M, RaffaelloD’A (2012) Real-time trajectory generation for interception maneuvers with quadrocopters. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 7. - 12.10.2012; Vilamoura. IEEE; 2012. p. 4979-4984. DOI:10.1109/IROS.2012.6386093

  3. M. Q. Lindsey M Q, Mellinger D, Kumar V (2012) Construction of cubic structures with quadrotor teams. In: Proceedings of Robotics: Science and Systems (RSS); Los Angeles, USA. MIT Press; 2012. p. 177-184

  4. Grzonka S, Grisetti G, Burgard W (2009) Towards a navigation system for autonomous indoor flying. In: IEEE International Conference on Robotics and Automation (ICRA); 12. - 17.5.2009; Kobe. IEEE; 2009. p. 2878-2883. DOI:10.1109/ROBOT.2009.5152446

  5. Ascending technologies [Internet]. 2016 . Available from: http://www.asctec.de/

  6. Krishnakumar R, Rasheed AM, Kumar KS, \(>>\) ””, October 21, (2015) Enhanced hover control of quad tilt frame UAV under windy conditions. International Journal of Advanced Robotic Systems. 2015:1–14. doi:10.5772/61231

  7. Krajník T, Vonásek V, Fišer D, Faigl J (2011) AR-Drone as a Platform for Robotic Research and Education. Communications in Computer and Information Science. 161:172–186

    Article  Google Scholar 

  8. Rullan-Lara JL, Sanahuja G, Lozano R, Salazar S, Garcia-Hernandez R, Ruz-Hernandez JA (2013) Indoor Localization of a Quadrotor Based on WSN: A Real-Time Application. International Journal of Advanced Robotic Systems. 10:48. doi:10.5772/53748

    Article  Google Scholar 

  9. Kim SJ, Kim BK (2012) Dynamic Ultrasonic Hybrid Localization System for Indoor Mobile Robots. IEEE Transactions on Industrial Electronics. 60(20):4562–4573. doi:10.1109/TIE.2012.2216235

    Google Scholar 

  10. Droeschel D, Schreiber M, Behnke S (2013) “.” UAV-g 8/2013. (2013). Omnidirectional perception for Lightweight UAVs using a continuously rotating 3D laser scanner. In: UAV-g 8/2013; 4. – 6.9. 2013; Rostock, Germany. The international archives of the photogrammetry, remote sensing and spatial information sciences, XL-1 W 2; 2013. p. 107-112. DOI:10.5194/isprsarchives-XL-1-W2-107-2013

  11. Engel J, Sturm J, Cremers D (2012) Accurate figure flying with a quadrocopter using onboard visual and inertial sensing. In: Workshop on Visual Control of Mobile Robots /ViCoMoR at the IEEE/RJS International Conference of Inteligent Robots and Sytems (IROS); 7.-12.10.2012; Vilamoura, Portugal. IEEE; 2012

  12. Zingg S, Scaramuzza D, Weiss S, Siegwart R (2010) MAV navigation through indoor corridors using optical flow. In: Robotics and Automation; 3-7 May 2010; Anchorage, AK. 2010. p. 3361 - 3368. DOI:10.1109/ROBOT.2010.5509777

  13. Eberli D et al (2011) Vision based position control for MAVs using one single circular landmark. Journal of Intelligent & Robotic Systems. 61(1):495–512. doi:10.1007/s10846-010-9494-8

    Article  Google Scholar 

  14. Lamberti F et al (2013) Mixed marker-based/marker-less visual odometry system for mobile robots. International Journal of Advanced Robotic Systems. 10(1):1–11. doi:10.5772/56577

    Article  Google Scholar 

  15. Hartmann P, Ben C, Moormann D (2014) Naviagation for Vertical Precision Landing Based on Optical Tracking of a Spatial Retroreflective Marker Array. In: 29th Congress of the International Council of the Aeronautical Sciences; 7-12 September; St. Petersburg, Russia. 2014. p. pp. 1-8

  16. Muñoz-Salinas, Rafael, et al (2016) “Mapping and Localization from Planar Markers.” arXiv preprint arXiv:1606.00151

  17. Garrido-Jurado S et al (2014) Automatic generation and detection of highly reliable fiducial markers under occlusion. Journal Pattern Recognition. 47(6):2280–2292. doi:10.1016/j.patcog.2014.01.005

    Article  Google Scholar 

  18. Kendoul F (2012) Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems. Journal of Field Robotics. 29(2):315–378. doi:10.1002/rob.20414

    Article  Google Scholar 

  19. Derafa L, Madani T, Benallegue A (2006) Dynamic Modelling and Experimental Identification of Four Rotors Helicopter Parameters. In: Proceedings of the IEEE International Conference on Industrial Technology; 15.-17.12.2006; Mumbai, India. IEEE; 2006. p. 1834-1839. DOI:10.1109/ICIT.2006.372515

  20. OstafewCh J, Schoellig AP, Barfoot TD (2014) Learning-based nonlinear model predictive control to improve vision-based mobile robot path-tracking in challenging outdoor environments. In: IEEE International Conference on Robotics and Automation (ICRA); 31.5. - 7.6.2014; Hong Kong. IEEE; 2014. p. 4029-4036. DOI:10.1109/ICRA.2014.6907444

  21. Gautam D, Ha Ch (2013) Control of a quadrotor using a smart self-tuning fuzzy PID controller. International Journal of Advanced Robotic Systems. 10:1–9. doi:10.5772/5691

    Article  Google Scholar 

  22. Poundsa P, Mahonyb R, Corkec P (2010) Modelling and control of a large quadrotor robot. Control Engineering Practice. 18(7):691–699. doi:10.1016/j.conengprac.2010.02.008

    Article  Google Scholar 

  23. Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies. 7(1):1–13

    Article  MATH  Google Scholar 

  24. Szlachetko B, Lower M, Nguyen NT, Hoang K, Jȩdrzejowicz P (2012) On Quadrotor Navigation Using Fuzzy Logic Regulators, Computational Collective Intelligence. Technologies and Applications: 4th International Conference, ICCCI 2012, Ho Chi Minh City, Vietnam, November 28–30, 2012. Proceedings, Part I

  25. Indrawati V, Prayitno A, Kusuma T A (2015) Waypoint Navigation of AR.Drone Quadrotor Using Fuzzy Logic Controller, TELKOMNIKA, Vol.13, No.3, September 2015, pp. \(930\sim 939\)

Download references

Acknowledgements

The authors wish to thank the project VEGA 459 1/0464/15 for its support. This work was supported by the Slovak Research and Development Agency under the contract No. APVV-15-0750.

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering and Informatics, Department of Electrical Engineering and Mechatronics, Technical University of Kosice, Letna 9, 042 00, Kosice, Slovakia

    Jan Bacik, Pavol Fedor & Daniela Perdukova

  2. Faculty of Mechanical Engineering, Department of Automation, Mechatronics and Robotics, Technical University of Kosice, Park Komenskeho 8, 042 00, Kosice, Slovakia

    Frantisek Durovsky

Authors
  1. Jan Bacik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Frantisek Durovsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pavol Fedor
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daniela Perdukova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jan Bacik.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bacik, J., Durovsky, F., Fedor, P. et al. Autonomous flying with quadrocopter using fuzzy control and ArUco markers. Intel Serv Robotics 10, 185–194 (2017). https://doi.org/10.1007/s11370-017-0219-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11370-017-0219-8

Keywords

Search

Navigation