Skip to main content

A Preliminary Study on Attitude Measurement Systems Based on Low Cost Sensors

  • Conference paper
  • First Online:
R3 in Geomatics: Research, Results and Review (R3GEO 2019)

Abstract

The increasingly use of Autonomous Underwater Vehicles (AUVs) in several context led to a rapid development and enhancement of their technologies, allowing the automatization of many tasks. One of the most challenging tasks of AUVs still remains their robust positioning and navigation, since classical global positioning techniques are generally not available for their operations. Inertial Navigation System (INS) methods provide the vehicle current position and orientation integrating data acquired by the internal accelerometer and gyroscope. This system has the advantage of not needing to either send or receive signals from other systems; however, among the errors the sensors are mainly affected by, the most critical one is related to their drift, which makes the position error growing over time. The attenuation of the effect of these problematics is generally achieved combining different positioning methods, as for example acoustic- or geophysical-based ones. An accurate estimation of the device orientation is anyway necessary to get satisfying results in terms of position and autonomous navigation. In this paper, a preliminary study on the use of smartphone low-cost sensors to perform attitude estimation is presented. With the final aim of developing a cheaper and more accessible underwater positioning system, a first analysis is conducted to verify the accuracy of the attitude angles obtained by the integration of smartphone data acquired in different operative settings. Different filtering methods will be employed.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Paull, L., Saeedi, S., Seto, M., Li, H.: AUV navigation and localization: a review. IEEE J. Oceanic Eng. 39(1), 131–149 (2013)

    Article  Google Scholar 

  2. Fanelli, F., Monni, N., Palma, N., Ridolfi, A.: Development of an ultra short baseline–aided buoy for underwater targets localization. Proc. Inst. Mech. Eng. Part M: J. Eng. Maritime Environ. 233(4) (2019). https://doi.org/10.1177/1475090219825768

  3. Wang, L., Pang, S.: AUV navigation based on inertial navigation and acoustic positioning systems. In: OCEANS 2018 MTS/IEEE Charleston, pp. 1–8. IEEE (2018)

    Google Scholar 

  4. Quintas, J., Teixeira, F.C., Pascoal, A.: AUV geophysical navigation using magnetic data—the MEDUSA GN system. In: 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), pp. 1122–1130. IEEE (2018)

    Google Scholar 

  5. Guth, F., Silveira, L., Botelho, S., Drews, P., Ballester, P.: Underwater SLAM: challenges, state of the art, algorithms and a new biologically-inspired approach. In: 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, pp. 981–986. IEEE (2014)

    Google Scholar 

  6. Salmony, P.: http://philsal.co.uk/projects/imu-attitude-estimation. Accessed September 2019

  7. Bao, J., Li, D., Qiao, X., Rauschenbach, T.: Integrated navigation for autonomous underwater vehicles in aquaculture: a review. Inf. Process. Agric. 7(1), 139–151 (2020)

    Google Scholar 

  8. Ludwig, S.A., Jiménez, A.R.: Optimization of gyroscope and accelerometer/magnetometer portion of basic attitude and heading reference system. In: 2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), pp. 1–4. IEEE (2018)

    Google Scholar 

  9. Ko, N.Y., Jeong, S.: Attitude estimation and DVL based navigation using low-cost MEMS AHRS for UUVs. In: 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 605–607. IEEE (2014)

    Google Scholar 

  10. Kos, A., Tomažič, S., Umek, A.: Evaluation of smartphone inertial sensor performance for cross-platform mobile applications. Sensors 16(4), 477 (2016)

    Article  Google Scholar 

  11. Piras, M., Lingua, A., Dabove, P., Aicardi, I.: Indoor navigation using Smartphone technology: a future challenge or an actual possibility? In: 2014 IEEE/ION Position, Location and Navigation Symposium-PLANS 2014, pp. 1343–1352. IEEE (2014)

    Google Scholar 

  12. Patonis, P., Patias, P., Tziavos, I., Rossikopoulos, D., Margaritis, K.: A fusion method for combining low-cost IMU/Magnetometer outputs for use in applications on mobile devices. Sensors 18(8), 2616 (2018)

    Article  Google Scholar 

  13. Guo, H., Hong, H.: Research on filtering algorithm of MEMS gyroscope based on information fusion. Sensors 19(16), 3552 (2019)

    Article  Google Scholar 

  14. Madgwick, S.O., Harrison, A.J., Vaidyanathan, R.: Estimation of IMU and MARG orientation using a gradient descent algorithm. In: 2011 IEEE International Conference on Rehabilitation Robotics, pp. 1–7. IEEE (2011)

    Google Scholar 

  15. Islam, T., Islam, M.S., Shajid-Ul-Mahmud, M., Hossam-E-Haider, M.: Comparison of complementary and Kalman filter based data fusion for attitude heading reference system. In: AIP Conference Proceedings, vol. 1919(1), p. 020002. AIP Publishing (2017)

    Google Scholar 

  16. Hedengren, J.D., Eaton, A.N.: Overview of estimation methods for industrial dynamic systems. Optim. Eng. 18(1), 155–178 (2015). https://doi.org/10.1007/s11081-015-9295-9

    Article  MATH  Google Scholar 

  17. The MathWorks, Inc. https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/submissions/40876/versions/8/previews/sensorgroup/Examples/html/CapturingAzimuthRollPitchExample.html. Accessed September 2019

  18. The MathWorks, Inc. Homepage. https://www.mathworks.com/. Accessed April 2020

  19. Loebis, D., Sutton, R., Chudley, J., Naeem, W.: Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system. Control Eng. Pract. 12(12), 1531–1539 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fabiana Di Ciaccio .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Di Ciaccio, F., Gaglione, S., Troisi, S. (2020). A Preliminary Study on Attitude Measurement Systems Based on Low Cost Sensors. In: Parente, C., Troisi, S., Vettore, A. (eds) R3 in Geomatics: Research, Results and Review. R3GEO 2019. Communications in Computer and Information Science, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-62800-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62800-0_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62799-7

  • Online ISBN: 978-3-030-62800-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics