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Development and Estimation of Low Price-Small-Autopilot UAS for Geo-spatial Information Aquisition

지형정보획득용 저가 소형 자동항법 UAS개발 및 평가

  • 한승희 (공주대학교 건설환경공학부)
  • Received : 2014.04.11
  • Accepted : 2014.05.21
  • Published : 2014.08.01

Abstract

Recent technological advances in wireless networks and microelectromechanical systems (MEMS) have led to the development of different types of mini-UAVs and their utilizations in various ways. This study endeavors to develop a low-cost mini-UAV with autonomous flight capability, in order to obtain geospatial information of a small or medium-sized area, and also assess its flight stability by comparing the predetermined flight paths against the actual flight paths. Based on a post-development flight test, stable flight has been proven achievable as follows: the maximum endurance speed is 1 hour, the flying distance is 50km, the horizontal accuracy of flight paths is about ${\pm}6{\sim}8m$, and the altitude accuracy is about ${\pm}8m$. Therefore, it is deemed that high-resolution images which can be utilized for geospatial information are obtainable. This indicates that a UAV flying at an altitude of 200m can acquire images across a $2km{\times}3km$ area on the ground within 25 minutes, which validates its high usability for obtaining high-solution images at low altitudes in the future.

무선통신(wireless networks)과 마이크로메카트로닉스 시스템(MEMS; microelectromechanical system)의 발달로 다양한 소형 자동항법 UAV가 개발되어 다양한 목적으로 활용되고 있다. 본 연구에서는 중소규모지역에 대한 지형정보획득을 목적으로 저가의 소형 자율항법 UAV를 개발하고 사전계획된 비행 루트와 실제 비행한 경로를 비교함으로써 비행의 안정성을 평가하였다. 개발 후 비행테스트 결과, 최대항속시간은 1시간, 비행거리는 50km, 비행항로의 수평정확도는 약 ${\pm}6{\sim}8m$, 고도정확도는 약 ${\pm}8m$로 안정된 비행이 가능하였으므로 지형정보에 활용할 수 있는 고해상영상의 획득이 가능한 것으로 판단되었다. 이는 200m의 고도로 비행할 경우 $2km{\times}3km$의 지상촬영범위를 약25분 내에 촬영이 가능하다는 의미로 향후 저고도 고해상영상의 획득목적으로 활용이 기대된다.

Keywords

References

  1. ALPH($\alpha$)Micro (2014). LEA-5H - u-blox 5 programmable GALILEOready GPS module, Available at: http://www.alphamicro.net/ franchises/u-blox/ lea-5h.aspx (Accessed: April 9, 2014).
  2. Calvin, C. (2009). "AGGIENAV: A small well integrated navigation sensor system for small unmanned aerial vehicle."Proceedings of the ASME, IDETC/CIE.
  3. Calvin, C. and Han, Y. (2009). "Aggieair: An integrated and effective small multi-UAV command, control and data collection architecture."Proceedings of the ASME.
  4. Calvin, C., Austin, M. J. and Chen, Y. Q. (2013). "Fractionalorder complementary filters for small unmanned aerial system navigation."2013 Proceeding of International Conference on Unmanned Aircraft Systems (ICUAS), pp. 28-31.
  5. Calvin, C., Brandon, S., Christopher, M. and Coffin (2012). "A payload verification and management framework for small UAVbased personal remote sensing systems."978-1-4673-0163-3 IEEE, pp. 184-189.
  6. Chao, H. Y., Cao, Y. C. and Chen, Y. Q. (2010c). "Autopilots for small unmanned aerial vehicles: A Survey."International Journal of Control, Automation, and Systems, Vol. 8, No. 1, pp. 36-44. https://doi.org/10.1007/s12555-010-0105-z
  7. Chao, H., Cao, Y. C. and Chen, Y. Q. (2010b). "Autopilots for small fixed-Wing unmanned air vehicles: A Survey."Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation.
  8. Chao, H., Luo, Y., Di, L. and Yang, Q. C. (2010a). "Roll-channel fractional order controller design for a small fixed-wing unmanned aerial vehicle."Control Engineering Practice, pp. 761-771.
  9. Chen, M. and Rincon, M. (2006). "Accurate electrical battery model capable of predicting runtime and i-v performance."IEEE Trans. Energy Convers, Vol. 21, No. 2, pp. 504-511. https://doi.org/10.1109/TEC.2006.874229
  10. Chingiz, H. and Halil, E. S. (2013). "Robust adaptive kalman filter for estimation of UAV dynamics in the presence of sensor/ actuator faults."Aerospace Science and Technology, Vol. 28, No. 1, pp. 376-383. https://doi.org/10.1016/j.ast.2012.12.003
  11. Egan G. K. (2006). "The use of infrared sensors for absolute attitude determination of unmanned aerial vehicles."Monash University, Technical Report MECSE-22-2006.
  12. Euston, P., Coote, R. M., Kim, J. H. and Hamel, T. (2008). "A complementary filter for attitude estimation of a fixed-wing UAV."In proceeding of: Intelligent Robots and Systems, IROS 2008. IEEE/RSJ International Conference.
  13. Gerasimos, G. R. (2012). "Nonlinear kalman filters and particle filters for integrated navigation of unmanned aerial vehicles." Robotics and Autonomous Systems, Vol. 60, No. 7, pp. 978-995. https://doi.org/10.1016/j.robot.2012.03.001
  14. Hai Chen, Xin-min and Yan, L. (2009). "A survey of autonomous control for UAV."Computational Intelligence Conference, Vol. 2, pp. 267-271.
  15. Han S. H. (2013). "A design proposal for economical autopiloted UAVs for acquiring geospatial information(I)."ISGIS Proceeding, pp. 156-157.
  16. Jang, J. S. and Liccardo, D. (2007). "Small UAV automation using MEMS."IEEE Aerospace and Electronic Systems Magazine, Vol. 22, No. 5, pp. 30-34.
  17. Jun, M., Roumeliotis and Sukhatme, S. I. (1999). "State estimation of an autonomous helicopter using Kalman filtering."Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 3, pp. 1346-1353.
  18. Kim, I. S. (2006). "The novel state of charge estimation method for lithium battery using sliding mode observer."Journal of Power Sources, Vol. 163, No. 1, pp. 584-590. https://doi.org/10.1016/j.jpowsour.2006.09.006
  19. LOAD $MicroStrain^{(R)}$ Sensing systems (2014). Inertial sensors, 3DM-GX2, Available at: http://www.microstrain.com/inertial/ 3DM-GX2 (Accessed: April 9, 2014).
  20. Masahiko, N., Chen, T., Afzal, A. and Shibasaki, R. (2008). "UAV borne mapping by multi sensor integration."The International archives of the photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII. Part. B1. pp. 1215-1221.
  21. Michal, P., Calvin, C. and Austin, J. (2014). "Battery state-of-charge based altitude controller for small, low cost multirotor unmanned aerial vehicles."Journal of Intelligent & Robotic Systems, Vol. 74, No. 1-2, pp. 193-207. https://doi.org/10.1007/s10846-013-9894-7
  22. Nathan, V. H., Calvin, C., Austin, M. J. and Chen, Y. Q. (2014). "A Survey and categorization of small low-cost unmanned aerial vehicle system identification."Journal of Intelligent & Robotic Systems, Vol. 74, No. 1-2, pp. 129-145. https://doi.org/10.1007/s10846-013-9931-6
  23. Paparazzi free pilot TWOG/v1.0 (2014). http://wiki.paparazziuav. org/wiki/ TWOG/v1.0 (Accessed: April 9, 2014).
  24. Pappalardo, J. (2003). "Unmanned aircraft roadmap reflects changing priorities."National Defense, Vol. 87, No. 392, pp. 30-36.
  25. Zeynep, C., Batu, D., Ozan, T. and Ilkay, Y. (2009). "Flight control system and integration for a small UAV testbed."ANKARA International Aerospace Conference, AIAC-2009-133, pp. 17-19.