Research Article
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GEZGİN ROBOTLARIN İÇ ORTAMDA SEYRÜSEFERİ İÇİN SIKI BAĞLI BİR BAŞ AÇISI VE KONUMLANDIRMA SİSTEMİ

Year 2021, , 346 - 355, 31.12.2021
https://doi.org/10.31796/ogummf.900354

Abstract

Bu çalışma, veri tümleştirme tekniklerinin, konumlandırma sistemlerinde gürbüz baş açısı ve konum bilgisi elde etmede etkinliğini göstermektedir. Önerilen system, gezgin robotun mutlak ve bağıl konumlandırma alt sistemlerini kullanarak baş açısı ve konum hesaplayan sıkı bağlı bir yapıya sahiptir. Bağıl konumlandırma alt sistemi, robotun odometre bilgilerini ve kinematik modelini kullanarak baş açısı ve konum bilgilerini elde eder. Mutlak konumlandırma sistemi ise, ultrasonik sinyalleri kullanarak konum ve aba baş açısı bilgisi elde etmektedir. Bu çalışmada, ilk olarak mutlak ve bağıl baş açısı bilgileri, geleneksel Kalman Filtresi ile tümleştirilerek gürbüz baş açısı bilgisi hesaplanmıştır. Daha sonra, bu gürbüz baş açısı bilgisi kullanılarak, bağıl konum ölçümünde düzeltme yapılmıştır. Son olarak, daha iyi konum bilgisi için, mutlak konum ve düzeltilmiş bağıl konumu tümleştirmek için uyarlanabilir bir Kalman filtresi uygulanmıştır. Deneysel çalışmada, sistemin konumsal doğruluğu ve hassasiyeti, test ortamı için sırasıyla 63 mm ve % 86 (konum hatası <100mm için) olarak elde edilmiştir. Önerilen sistem daha güvenilir, sürekli ve daha az gürültülü baş açısı ve konum bilgisi vermekte olup iç ortamlardaki birçok görev için uygundur.

Supporting Institution

Tübitak Teydeb

Project Number

7100932, 7120742

References

  • Afzal, M. H., Renaudin, V., & Lachapelle, G. (2011, September). Magnetic field based heading estimation for pedestrian navigation environments. In 2011 International Conference on Indoor Positioning and Indoor Navigation (pp. 1-10). IEEE.
  • Atia, M. M., Noureldin, A., & Korenberg, M. J. (2012). Dynamic propagation modeling for mobile users' position and heading estimation in wireless local area networks. IEEE Wireless Communications Letters, 1(2), 101-104.
  • Chai, W., Chen, C., Edwan, E., Zhang, J., & Loffeld, O. (2012, March). INS/Wi-Fi based indoor navigation using adaptive Kalman filtering and vehicle constraints. In 2012 9th Workshop on Positioning, Navigation and Communication (pp. 36-41). IEEE.
  • Farid, Z., Nordin, R., & Ismail, M. (2013). Recent advances in wireless indoor localization techniques and system. Journal of Computer Networks and Communications, 2013.
  • Höflinger, F., Müller, J., Zhang, R., Reindl, L. M., & Burgard, W. (2013). A wireless micro inertial measurement unit (IMU). IEEE Transactions on instrumentation and measurement, 62(9), 2583-2595.
  • Kang, W., Nam, S., Han, Y., & Lee, S. (2012, September). Improved heading estimation for smartphone-based indoor positioning systems. In 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC) (pp. 2449-2453). IEEE.
  • Khyam, M. O., Xinde, L., Ge, S. S., & Pickering, M. R. (2017). Multiple access chirp-based ultrasonic positioning. IEEE Transactions on Instrumentation and Measurement, 66(12), 3126-3137.
  • Kim, S. J., & Kim, B. K. (2012). Dynamic ultrasonic hybrid localization system for indoor mobile robots. IEEE Transactions on Industrial Electronics, 60(10), 4562-4573.
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  • Liu, H., Darabi, H., Banerjee, P., & Liu, J. (2007). Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 37(6), 1067-1080.
  • Munguia, R., & Grau, A. (2011, September). An attitude and heading reference system (AHRS) based in a dual filter. In ETFA2011 (pp. 1-8). IEEE.
  • Priyantha, N. B. (2005). The cricket indoor location system (Doctoral dissertation, Massachusetts Institute of Technology).
  • Sun, C. J., Kuo, H. Y., & Lin, C. E. (2010, May). A sensor based indoor mobile localization and navigation using unscented Kalman filter. In IEEE/ION Position, Location and Navigation Symposium (pp. 327-331). IEEE.
  • Wang, D., Low, C., He, B., & Pham, M. (2004, December). Accurate positioning for real-time control purpose integration of GPS, NAV200 and encoder data. In ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. (Vol. 1, pp. 161-166). IEEE.
  • Xiao, W., Ni, W., & Toh, Y. K. (2011, September). Integrated Wi-Fi fingerprinting and inertial sensing for indoor positioning. In 2011 International Conference on Indoor Positioning and Indoor Navigation (pp. 1-6). IEEE.
  • Yayan, U., Yucel, H. & Yazici, A. (2015). A low cost ultrasonic based positioning system for the indoor navigation of mobile robots. Journal of Intelligent & Robotic Systems, 78(3), 541-552.
  • Yazici, A., Sipahioglu, A., & Parlaktuna, O. (2009). Heuristic-based dynamic route planning method for a homogeneous multi-robot team. Advanced Robotics, 23(3), 269-287.
  • Zhang, R., Hoflinger, F., & Reindl, L. (2012). Inertial sensor based indoor localization and monitoring system for emergency responders. IEEE Sensors Journal, 13(2), 838-848.
  • Zhuang, Y., Shen, Z., Syed, Z., Georgy, J., Syed, H., & El-Sheimy, N. (2014, May). Autonomous WLAN heading and position for smartphones. In Proceedings of IEEE/ION PLANS 2014 (pp. 1113-1121).

A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS

Year 2021, , 346 - 355, 31.12.2021
https://doi.org/10.31796/ogummf.900354

Abstract

This study shows the effectiveness of data fusion techniques to achieve robust heading and position information in localization systems. The proposed system that has tightly coupled structure calculates heading and position of the mobile robot using the absolute and relative positioning subsystems. The relative positioning subsystem obtains heading and position information by using the odometry information and kinematic model of the robot. Absolute positioning subsystem, calculates position and rough heading information using ultrasonic signals. In this study, firstly the robust heading information is calculated by combining absolute and relative heading with conventional Kalman Filter. And then the correction on the relative position measurement has been made by using this robust heading information. Finally, in order to better positional information, an adaptive Kalman filter is applied for fusing the the absolute position and the corrected relative position. In the experimental study, the positional accuracy and precision of the system is obtained as 63 mm and 86% (for positional error<100mm) respectively for the test environment. The proposed system gives more reliable, continuous and less noisy heading and position information and is suitable for many tasks in indoor environments.

Project Number

7100932, 7120742

References

  • Afzal, M. H., Renaudin, V., & Lachapelle, G. (2011, September). Magnetic field based heading estimation for pedestrian navigation environments. In 2011 International Conference on Indoor Positioning and Indoor Navigation (pp. 1-10). IEEE.
  • Atia, M. M., Noureldin, A., & Korenberg, M. J. (2012). Dynamic propagation modeling for mobile users' position and heading estimation in wireless local area networks. IEEE Wireless Communications Letters, 1(2), 101-104.
  • Chai, W., Chen, C., Edwan, E., Zhang, J., & Loffeld, O. (2012, March). INS/Wi-Fi based indoor navigation using adaptive Kalman filtering and vehicle constraints. In 2012 9th Workshop on Positioning, Navigation and Communication (pp. 36-41). IEEE.
  • Farid, Z., Nordin, R., & Ismail, M. (2013). Recent advances in wireless indoor localization techniques and system. Journal of Computer Networks and Communications, 2013.
  • Höflinger, F., Müller, J., Zhang, R., Reindl, L. M., & Burgard, W. (2013). A wireless micro inertial measurement unit (IMU). IEEE Transactions on instrumentation and measurement, 62(9), 2583-2595.
  • Kang, W., Nam, S., Han, Y., & Lee, S. (2012, September). Improved heading estimation for smartphone-based indoor positioning systems. In 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC) (pp. 2449-2453). IEEE.
  • Khyam, M. O., Xinde, L., Ge, S. S., & Pickering, M. R. (2017). Multiple access chirp-based ultrasonic positioning. IEEE Transactions on Instrumentation and Measurement, 66(12), 3126-3137.
  • Kim, S. J., & Kim, B. K. (2012). Dynamic ultrasonic hybrid localization system for indoor mobile robots. IEEE Transactions on Industrial Electronics, 60(10), 4562-4573.
  • Koo, W., Sung, S., & Lee, Y. J. (2009, August). Development of real-time heading estimation algorithm using magnetometer/IMU. In 2009 ICCAS-SICE (pp. 4212-4216). IEEE.
  • Kwon, W., Roh, K. S., & Sung, H. K. (2006, May). Particle filter-based heading estimation using magnetic compasses for mobile robot navigation. In Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. (pp. 2705-2712). IEEE.
  • Liu, H., Darabi, H., Banerjee, P., & Liu, J. (2007). Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 37(6), 1067-1080.
  • Munguia, R., & Grau, A. (2011, September). An attitude and heading reference system (AHRS) based in a dual filter. In ETFA2011 (pp. 1-8). IEEE.
  • Priyantha, N. B. (2005). The cricket indoor location system (Doctoral dissertation, Massachusetts Institute of Technology).
  • Sun, C. J., Kuo, H. Y., & Lin, C. E. (2010, May). A sensor based indoor mobile localization and navigation using unscented Kalman filter. In IEEE/ION Position, Location and Navigation Symposium (pp. 327-331). IEEE.
  • Wang, D., Low, C., He, B., & Pham, M. (2004, December). Accurate positioning for real-time control purpose integration of GPS, NAV200 and encoder data. In ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. (Vol. 1, pp. 161-166). IEEE.
  • Xiao, W., Ni, W., & Toh, Y. K. (2011, September). Integrated Wi-Fi fingerprinting and inertial sensing for indoor positioning. In 2011 International Conference on Indoor Positioning and Indoor Navigation (pp. 1-6). IEEE.
  • Yayan, U., Yucel, H. & Yazici, A. (2015). A low cost ultrasonic based positioning system for the indoor navigation of mobile robots. Journal of Intelligent & Robotic Systems, 78(3), 541-552.
  • Yazici, A., Sipahioglu, A., & Parlaktuna, O. (2009). Heuristic-based dynamic route planning method for a homogeneous multi-robot team. Advanced Robotics, 23(3), 269-287.
  • Zhang, R., Hoflinger, F., & Reindl, L. (2012). Inertial sensor based indoor localization and monitoring system for emergency responders. IEEE Sensors Journal, 13(2), 838-848.
  • Zhuang, Y., Shen, Z., Syed, Z., Georgy, J., Syed, H., & El-Sheimy, N. (2014, May). Autonomous WLAN heading and position for smartphones. In Proceedings of IEEE/ION PLANS 2014 (pp. 1113-1121).
There are 20 citations in total.

Details

Primary Language English
Subjects Computer Software
Journal Section Research Articles
Authors

Hikmet Yücel 0000-0001-7657-3567

Rifat Edizkan 0000-0002-5125-5631

Ahmet Yazici 0000-0001-5589-2032

Project Number 7100932, 7120742
Publication Date December 31, 2021
Acceptance Date September 4, 2021
Published in Issue Year 2021

Cite

APA Yücel, H., Edizkan, R., & Yazici, A. (2021). A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 29(3), 346-355. https://doi.org/10.31796/ogummf.900354
AMA Yücel H, Edizkan R, Yazici A. A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS. ESOGÜ Müh Mim Fak Derg. December 2021;29(3):346-355. doi:10.31796/ogummf.900354
Chicago Yücel, Hikmet, Rifat Edizkan, and Ahmet Yazici. “A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi 29, no. 3 (December 2021): 346-55. https://doi.org/10.31796/ogummf.900354.
EndNote Yücel H, Edizkan R, Yazici A (December 1, 2021) A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 29 3 346–355.
IEEE H. Yücel, R. Edizkan, and A. Yazici, “A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS”, ESOGÜ Müh Mim Fak Derg, vol. 29, no. 3, pp. 346–355, 2021, doi: 10.31796/ogummf.900354.
ISNAD Yücel, Hikmet et al. “A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS”. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 29/3 (December 2021), 346-355. https://doi.org/10.31796/ogummf.900354.
JAMA Yücel H, Edizkan R, Yazici A. A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS. ESOGÜ Müh Mim Fak Derg. 2021;29:346–355.
MLA Yücel, Hikmet et al. “A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, vol. 29, no. 3, 2021, pp. 346-55, doi:10.31796/ogummf.900354.
Vancouver Yücel H, Edizkan R, Yazici A. A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS. ESOGÜ Müh Mim Fak Derg. 2021;29(3):346-55.

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