Advertisement

Journal of Intelligent & Robotic Systems

, Volume 81, Issue 3–4, pp 531–549 | Cite as

Vision-aided Estimation of Attitude, Velocity, and Inertial Measurement Bias for UAV Stabilization

  • Shiyu Zhao
  • Feng Lin
  • Kemao Peng
  • Xiangxu Dong
  • Ben M. Chen
  • Tong H. Lee
Article

Abstract

This paper studies vision-aided inertial navigation of small-scale unmanned aerial vehicles (UAVs) in GPS-denied environments. The objectives of the navigation system are to firstly online estimate and compensate the unknown inertial measurement biases, secondly provide drift-free velocity and attitude estimates which are crucial for UAV stabilization control, and thirdly give relatively accurate position estimation such that the UAV is able to perform at least a short-term navigation when the GPS signal is not available. For the vision system, we do not presume maps or landmarks of the environment. The vision system should be able to work robustly even given low-resolution images (e.g., 160 ×120 pixels) of near homogeneous visual features. To achieve these objectives, we propose a novel homography-based vision-aided navigation system that adopts four common sensors: a low-cost inertial measurement unit, a downward-looking monocular camera, a barometer, and a compass. The measurements of the sensors are fused by an extended Kalman filter. Based on both analytical and numerical observability analyses of the navigation system, we theoretically verify that the proposed navigation system is able to achieve the navigation objectives. We also show comprehensive simulation and real flight experimental results to verify the effectiveness and robustness of the proposed navigation system.

Keywords

Unmanned aerial vehicle Vision-based navigation Homography Attitude estimation Observability analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cai, G., Chen, B.M., Lee, T.H.: Unmanned Rotorcraft Systems. Springer, New York (2011)CrossRefzbMATHGoogle Scholar
  2. 2.
    Phang, S.K., Li, K., Yu, K.H., Chen, B.M., Lee, T.H.: Systematic design and implementation of a micro unmanned quadrotor system. Unmanned Syst. 2(2), 121–141 (2014)CrossRefGoogle Scholar
  3. 3.
    Kim, J., Sukkarieh, S.: Autonomous airborne navigation in unknown terrain environments. IEEE Trans. Aerosp. Electron. Syst. 40, 1031–1045 (2004)CrossRefGoogle Scholar
  4. 4.
    Wu, A.D., Johnson, E.N., Proctor, A.A.: Vision-aided inertial navigation for flight control. AIAA J. Aerosp. Comput. Inf. Commun. 2(9), 348–360 (2005)CrossRefGoogle Scholar
  5. 5.
    Kim, J., Sukkarieh, S.: Real-time implementation of airborne inertial-SLAM. Robot. Auton. Syst. 55, 62–71 (2007)CrossRefGoogle Scholar
  6. 6.
    Bryson, M., Sukkarieh, S.: Observability analysis and active control for airborne SLAM. IEEE Trans. Aerosp. Electron. Syst. 1, 261–280 (2008)CrossRefGoogle Scholar
  7. 7.
    Taylor, C.N., Veth, M.J., Raquet, J.F., Miller, M.M.: Comparison of two image and inertial sensor fusion techniques for navigation in unmapped environments. IEEE Trans. Aerosp. Electron. Syst. 47(2), 946–958 (2011)CrossRefGoogle Scholar
  8. 8.
    Zhang, J., Liu, W., Wu, Y.: Novel technique for vision-based UAV navigation. IEEE Trans. Aerosp. Electron. Syst. 47(4), 2731–2741 (2011)CrossRefGoogle Scholar
  9. 9.
    Scaramuzza, D., Fraundorfer, F.: Visual odometry: Part I - the first 30 years and fundamentals. IEEE Robot. Autom. Mag. 18(4), 80–92 (2011)CrossRefGoogle Scholar
  10. 10.
    Peng, K., Zhao, S., Lin, F., Chen, B.M.: Vision based target tracking/following and estimation of target motion. In: Proceedings of the 2013 AIAA Guidance, Navigation and Control Conference, Boston, USA (2013)Google Scholar
  11. 11.
    Lin, F., Ang, K.Z.Y., Wang, F., Chen, B.M., Lee, T.H., Yang, B., Dong, M., Dong, X., Cui, J., Phang, S.K., Wang, B., Luo, D., Peng, K., Cai, G., Zhao, S., Yin, M., Li, K.: Development of an unmanned coaxial rotorcraft for the darpa uavforge challenge. Unmanned Syst. 1(2), 247–258 (2013)CrossRefGoogle Scholar
  12. 12.
    Wang, F., Liu, P., Zhao, S., Chen, B.M., Phang, S.K., Lai, S., Pang, T., Wang, B., Cai, C., Lee, T.H.: Development of an unmanned helicopter for verticle replenishment. Unmanned Syst. 3(1), 63–87 (2015)Google Scholar
  13. 13.
    Bonin-Font, F., Ortiz, A., Oliver, G.: Visual navigation for mobile robots: A survey. J. Intell. Robot. Syst. 53, 263–296 (2008)CrossRefGoogle Scholar
  14. 14.
    Conte, G., Doherty, P.: Vision-based unmanned aerial vehicle navigation using geo-referenced information. EURASIP J. Adv. Signal Process. 1–18 (2009)Google Scholar
  15. 15.
    Caballero, F., Merino, L., Ferruz, J., Ollero, A.: Vision-based odometry and SLAM for medium and high altitude flying UAVs. J. Intell. Robot. Syst. 54, 137–161 (2009)CrossRefGoogle Scholar
  16. 16.
    Kaiser, M.K., Gans, N.R., Dixon, W.E.: Vision-based estimation for guidance, navigation, and control of an aerial vehicle. IEEE Trans. Aerosp. Electron. Syst. 46(3), 137–161 (2010)CrossRefGoogle Scholar
  17. 17.
    Mourikis, A.I., Trawny, N., Roumeliotis, S.I., Johnson, A.E., Ansar, A., Matthies, L.: Vision-aided inertial navigation for spacecraft entry, descent, and landing. IEEE Trans. Robot. 25(2), 264–280 (2009)CrossRefGoogle Scholar
  18. 18.
    Howard, A.M., Jones, B.M., Serrano, N.: Integrated sensing for entry, descent, and landing of a robotic spacecraft. IEEE Trans. Aerosp. Electron. Syst. 47(1), 295–304 (2011)CrossRefGoogle Scholar
  19. 19.
    Wang, F., Cui, J., Phang, S.K., Chen, B.M., Lee, T.H.: A mono-camera and scanning laser range finder based UAV indoor navigation system. In: Proceedings of the 2013 International Conference on Unmanned Aircraft Systems, pp. 693–700. Atlanta, USA (2013)Google Scholar
  20. 20.
    Ma, Y., Soatto, S., Kosecka, J., Sastry, S.: An Invitation to 3D Vision. Springer, New York (2004)CrossRefGoogle Scholar
  21. 21.
    Di, L., Fromm, T., Chen, Y.: A data fusion system for attitude estimation of low-cost miniature UAVs. J. Intell. Robot. Syst. (2011)Google Scholar
  22. 22.
    Shabayek, A.E.R., Demonceaux, C., Morel, O., Fofi, D.: Vision based UAV attitude estimation: Progress and insights. J. Intell. Robot. Syst. 65(1–4), 295–308 (2012)CrossRefGoogle Scholar
  23. 23.
    Martinelli, A: Vision and IMU data fusion: Closed-form solutions for attitude, speed, absolute scale, and bias determination. IEEE Trans. Robot. 28(1), 44–60 (2012)CrossRefMathSciNetGoogle Scholar
  24. 24.
    Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, ISBN: 0521540518 (2004)Google Scholar
  25. 25.
    Groves, P.D.: Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems. Artech House (2008)Google Scholar
  26. 26.
    Nardone, S.C., Aidala, V.J.: Observability criteria for bearings-only target motion analysis. IEEE Trans. Aerosp. Electron. Syst. 17(2), 162–166 (1981)CrossRefMathSciNetGoogle Scholar
  27. 27.
    Nardone, S.C., Lindgren, A.G., Gong, K.F.: Fundamental properties and performance of conventional bearings-only target motion analysis. IEEE Trans. Autom. Control 29(9), 775–787 (1984)CrossRefGoogle Scholar
  28. 28.
    Zhao, S., Chen, B.M., Lee, T.H.: Optimal placement of bearing-only sensors for target localization. In: Proceedings of the 2012 American Control Conference, pp. 5108–5113. Montreal, Canada (2012)Google Scholar
  29. 29.
    Zhao, S., Chen, B.M., Lee, T.H.: Optimal sensor placement for target localization and tracking in 2D and 3D. Int. J. Control. 86(10), 1687–1704 (2013)CrossRefMathSciNetGoogle Scholar
  30. 30.
    Michaelsen, E., Kirchhof, M., Stilla, U.: Sensor pose inference from airborne videos by decomposing homography estimates. In: Proceedings of the 2011 Asian Control Conference, pp. 211–216. Kaohsiung, Taiwan (2011)Google Scholar
  31. 31.
    Dong, X., Chen, B.M., Cai, G., Lin, H., Lee, T.H.: Development of a comprehensive software system for implementing cooperative control of multiple unmanned aerial vehicles. Int. J. Robot. Autom. 26(1), 49–63 (2011)Google Scholar
  32. 32.
    Liu, P., Dong, X., Chen, B.M., Lee, T.H.: Development of an enhanced ground control system for unmanned aerial vehicles. In: Proceedings of the IASTED International Conference on Engineering and Applied Science, pp. 136–143. Colombo, Sri Lanka (2012)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Shiyu Zhao
    • 1
  • Feng Lin
    • 2
  • Kemao Peng
    • 2
  • Xiangxu Dong
    • 2
  • Ben M. Chen
    • 1
  • Tong H. Lee
    • 1
  1. 1.Department of Electrical, Computer EngineeringNational University of SingaporeSingaporeSingapore
  2. 2.Temasek LaboratoriesNational University of SingaporeSingaporeSingapore

Personalised recommendations