BibTex RIS Kaynak Göster

IMPROVED LASER-BASED NAVIGATION FOR MOBILE ROBOTS

Yıl 2011, Cilt: 3 Sayı: 1, 79 - 92, 01.03.2011

Öz

An autonomous mobile system can operate as a service robot in various environments. In many man-made environments like buildings, there exist a lot of glass panes, such as windows, doors and glass walls. This can make robotics tasks more complicated, since one of the most popular sensor systems, namely laser range finder, faces problems with measuring correct distances when hitting glass surfaces. In this paper the behavior of a laser scanner with respect to glass surface is modeled using a probabilistic approach. This sensor model is employed to improve mapping and localization of a mobile robot in an office environment. Both of the applications have been tested with a real robot

Kaynakça

  • A. Aboshosha and A. Zell. Disambiguating robot positioning using laser and geomagnetic signatures. In proceedings of IAS-8, 2004.
  • A. Diosi and L. Kleeman. Advanced sonar and laser range finder fusion for simultaneous localization and mapping. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1854–1859, October 2 2004.
  • E. Fabrizi, G. Oriolo, S. Panzieri, and G. Ulivi. Enhanced uncertainty modeling for robot localisation. 7th Int. Symp. on Robotics with Applications (ISORA98).
  • E. Hecht. OPTICS, chapter 4. Addison Wesley, fourth edition, 2002.
  • X. C. Lai, C. Y. Kong, S. S. Ge, and A. A. Mamun. Online map building for autonomous mobile robots by fusing laser and sonar data. Proceedings of the IEEE International Conference on Mechatronics & Automation, 2005.
  • D. Lee, W. Chung, and M. Kim. Probabilistic localization of the service robot by map matching algorithm. In Proc. of International Conference on Control, Automation and Systems (ICCAS’2002), pages 1667–1627, 2002.
  • S. Z. Li. Markov random field modeling in image analysis. Springer Verlag, 2nd edition, 2001.
  • K. Lingemann, A. Nüchter, J. Hertzberg, and H. Surmann. Highspeed laser localization for mobile robots. Robotics and Autonomous System, 51:275–296, 2005.
  • L. R. Muñoz and J. A. Pimentel. Robust local localization of a mobile robot using a 180_ 2-d laser range finder. in Proceedings of IEEE Sixth Mexican International Conference on Computer Science, 2005.
  • W. B. Sebastian Thrun and D. Fox. Probabilistic Robotics. MIT Press, 2005.
  • D. W. Seward, S. D. Quayle, K. Zied, and C. Pace. Data interpretation from leuze rotoscan sensor for robot localisation and environment mapping. ISARC, 2002.
  • S. Thrun, W. Burgard, and D. Fox. A probabilistic approach to concurrent mapping and localization for mobile robots. Machine Learning and Autonomous Robots, Kluwer Academic Publishers, Boston, pages 1–25, 1998.
  • S. Yang and C. Wang. Dealing with laser scanner failure: Mirrors and windows. IEEE International Conference on Robotics and Automation, May 19-23 2008.
Yıl 2011, Cilt: 3 Sayı: 1, 79 - 92, 01.03.2011

Öz

Kaynakça

  • A. Aboshosha and A. Zell. Disambiguating robot positioning using laser and geomagnetic signatures. In proceedings of IAS-8, 2004.
  • A. Diosi and L. Kleeman. Advanced sonar and laser range finder fusion for simultaneous localization and mapping. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1854–1859, October 2 2004.
  • E. Fabrizi, G. Oriolo, S. Panzieri, and G. Ulivi. Enhanced uncertainty modeling for robot localisation. 7th Int. Symp. on Robotics with Applications (ISORA98).
  • E. Hecht. OPTICS, chapter 4. Addison Wesley, fourth edition, 2002.
  • X. C. Lai, C. Y. Kong, S. S. Ge, and A. A. Mamun. Online map building for autonomous mobile robots by fusing laser and sonar data. Proceedings of the IEEE International Conference on Mechatronics & Automation, 2005.
  • D. Lee, W. Chung, and M. Kim. Probabilistic localization of the service robot by map matching algorithm. In Proc. of International Conference on Control, Automation and Systems (ICCAS’2002), pages 1667–1627, 2002.
  • S. Z. Li. Markov random field modeling in image analysis. Springer Verlag, 2nd edition, 2001.
  • K. Lingemann, A. Nüchter, J. Hertzberg, and H. Surmann. Highspeed laser localization for mobile robots. Robotics and Autonomous System, 51:275–296, 2005.
  • L. R. Muñoz and J. A. Pimentel. Robust local localization of a mobile robot using a 180_ 2-d laser range finder. in Proceedings of IEEE Sixth Mexican International Conference on Computer Science, 2005.
  • W. B. Sebastian Thrun and D. Fox. Probabilistic Robotics. MIT Press, 2005.
  • D. W. Seward, S. D. Quayle, K. Zied, and C. Pace. Data interpretation from leuze rotoscan sensor for robot localisation and environment mapping. ISARC, 2002.
  • S. Thrun, W. Burgard, and D. Fox. A probabilistic approach to concurrent mapping and localization for mobile robots. Machine Learning and Autonomous Robots, Kluwer Academic Publishers, Boston, pages 1–25, 1998.
  • S. Yang and C. Wang. Dealing with laser scanner failure: Mirrors and windows. IEEE International Conference on Robotics and Automation, May 19-23 2008.
Toplam 13 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA44DR54FG
Bölüm Araştırma Makalesi
Yazarlar

Muhammad Awaıs Bu kişi benim

Yayımlanma Tarihi 1 Mart 2011
Yayımlandığı Sayı Yıl 2011 Cilt: 3 Sayı: 1

Kaynak Göster

IEEE M. Awaıs, “IMPROVED LASER-BASED NAVIGATION FOR MOBILE ROBOTS”, UTBD, c. 3, sy. 1, ss. 79–92, 2011.

Dergi isminin Türkçe kısaltması "UTBD" ingilizce kısaltması "IJTS" şeklindedir.

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