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Landmark Sequence Data Association for Simultaneous Localization and Mapping of Robots Cover

Landmark Sequence Data Association for Simultaneous Localization and Mapping of Robots

Cybernetics and Information Technologies
Volume 14 (2014): Issue 3 (September 2014)
By:  and    
Open Access
|Nov 2014
References

References

  1. 1. Uyen, H. S. V., J. W. Jeon. Combine Kalman Filter and Particle Filter to Improve Color Tracking Algorithm. - In: Proc. of International Conference on Control, Automation and Systems 2007, 558-561.
    Search in Google Scholar
  2. 2. Anati, R., D. Scar amu z z a, K. G. Derpanis, K. Daniilidis. Robot Localization Using Soft Object Detection. - In: Proc. of IEEE International Conference on Robotics and Automation (ICRA’2012), 2012, 4992-4999.
    Open DOISearch in Google Scholar
  3. 3. Ivanjko, E., M. Uasak, I. Petrovic. Kalman Filter Theory Based Mobile Robot Pose Tracking Using Occupancy Grid Maps. - In: Proc. of International Conference on Control and Automation (ICCA’2005), 2005, 869-874.
    Search in Google Scholar
  4. 4. Smith, R., P. M. Chesseman. Estimating Uncertain Spatial Relationships in Robotics. - Ulncertainty in Artificial Intelligence, 1988, 435-461.
    Open DOISearch in Google Scholar
  5. 5. Smith, R., M. Self, P. Cheeseman. A Stochastic Map for Uncertain Spatial Relationships. - In: Proc. of IEEE: International Symposium of Robotics Research, 1987, 467-474.
    Search in Google Scholar
  6. 6. Bailey, T., J. Nieto, J. Guivant, et al. Consisteney of the EKF-SLAM Algorithm. - In: Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems. Beijing: IEEE, 2006, 3562-3568.
    Search in Google Scholar
  7. 7. Bailey, T., J. Nieto, E. Nebot. Consistency of the Fast SLAM Algorithm. - In: Proc. of IEEE Int. Conf. on Robotics and Automation. Orlando: IEEE, 2006, 424-429.
    Search in Google Scholar
  8. 8. Neira, J., J. D. Tard´os. Data Association in Stochastic Mapping Using the Joint Compatibility Test. - IEEE Transactions on Robotics and Automation, Vol. 17, 2001, No 6, 890-897.
    Open DOISearch in Google Scholar
  9. 9. Yi, Yingmin, Ding Liu. Color-State-Noise Simultaneous Localisation and Mapping for Wheel Robots. - Chinese Journal of Electronics, Vol. 38, 2010, No 6, 1339-1243.
    Search in Google Scholar
  10. 10. Singer, R. A, R. G. Sea. A New Filter for Optimal Trackingin Dense Multitarget Environments. - In: Proc. of 9th Allerton Conference Circuit and System Theory, Urbana- Champaign, USA, 1971, 201-211.
    Search in Google Scholar
  11. 11. Watanabe, K., C. D. Pathiranage, K. Izumi. T-S Fuzzy Model Adopted SLAM Algorithm with Linear Programming Based Data Association for Mobile Robots. - In: Proc. of IEEE International Symposium on Industrial Electronics (ISIE’2009), 2009, 244-249.
    Open DOISearch in Google Scholar
  12. 12. Wong, R. H., Xiao Jizhong, S. L. Joseph. A Robust Data Association for Simultaneous Localization and Mapping in Dynamic Environments. - In: Proc. of IEEE International Conference on Information and Automation (ICIA’2010), 2010, 470-475.
    Open DOISearch in Google Scholar
  13. 13. Shu, Yuan, Yuan Donghui, Sun Jizhou, Liu Yongbo, Li Jing, Yuan Lin. The Application of AC-GA on Multi-Sensor Multi-Target Tracking. - Chinese Journal of Electronics, Vol. 41, 2013, No 3, 609-614.
    Search in Google Scholar
  14. 14. Maksarov, D, H. Durrant-Whyte. Mobile Vehicle Navigation in Unknown Environments: A Multiple Hypothesis Approach. - IEEE Proc. Control Theory Application, Vol. 142, 1995, No 4, 385-391.
    Open DOISearch in Google Scholar
  15. 15. Guivant, J., E. Nebot. Optimization of the Simultaneous Localization and Map-Building Algorithm for Real-Time Implementation. - IEEE Transactions on Robotics and Automation, Vol. 17, 2003, No 3, 242-257.
    Open DOISearch in Google Scholar
  16. 16. Castellanos, J. A., J. M. M. Montiel, J. Neira, et al. The SPmap: A Probabilistic Framework for Simultaneous Localization and Map Building. - IEEE Transactions on Robotics and Automation, Vol. 15, 1999, No 5, 948-952.
    Open DOISearch in Google Scholar
  17. 17. Bailey, T., E. Nebot. Localisation in Large-Scale Environments. - Robotics and Autonomous Systems, Vol. 37, 2001, No 4, 261-281.
    Open DOISearch in Google Scholar
  18. 18. Bailey, T., E. M. Nebot, J. K. Rosenblatt, H. F. Durrant-Whyte. Data Association for Mobile Robot Navigation: A Graph Theoretic Approach. - In: Proc. of IEEE International Conference on Robotics and Automation, 2000, 2512-2517.
    Search in Google Scholar
  19. 19. Jeong, C. S., M. H. Kim. Fast Parallel Simulated Annealing for Traveling Salesman Problem. - In: Proc. of International Joint Conference (IJCNN’1990), San Diego, CA, 1990, 947-953.
    Open DOISearch in Google Scholar
  20. 20. Bar-Shalom, Y., X. R. L i, T. Kirubarajan. Estimation with Applications to Tracking and Navigation. Toronto, John Wiley and Sons, 2001, 234-235.
    Open DOISearch in Google Scholar
  21. 21. Krajčí, V., N. Stojković. Improvement of Robot Trajectory Tracking by Using Nonlinear Control Methods. - Engineering Review, Vol. 26, 2006, No 1, 7-17.
    Search in Google Scholar
DOI: https://doi.org/10.2478/cait-2014-0035 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702 (formerly 1314-4081)
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Language: English
Page range: 86 - 95
Published on: Nov 5, 2014
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Keywords:
Landmark sequence,
data association,
simultaneous localization and mapping,
robots
Related subjects:
Computer sciences,
Information technology

© 2014 Yingmin Yi, Ying Huang, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 14 (2014): Issue 3 (September 2014)
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