Uncertainty models of vision sensors in mobile robot positioning

Piotr Skrzypczyński

International Journal of Applied Mathematics and Computer Science (2005)

  • Volume: 15, Issue: 1, page 73-88
  • ISSN: 1641-876X

Abstract

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This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.

How to cite

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Skrzypczyński, Piotr. "Uncertainty models of vision sensors in mobile robot positioning." International Journal of Applied Mathematics and Computer Science 15.1 (2005): 73-88. <http://eudml.org/doc/207730>.

@article{Skrzypczyński2005,
abstract = {This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.},
author = {Skrzypczyński, Piotr},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {uncertainty; positioning; mobile robots; multi-agent systems; action planning; vision sensors},
language = {eng},
number = {1},
pages = {73-88},
title = {Uncertainty models of vision sensors in mobile robot positioning},
url = {http://eudml.org/doc/207730},
volume = {15},
year = {2005},
}

TY - JOUR
AU - Skrzypczyński, Piotr
TI - Uncertainty models of vision sensors in mobile robot positioning
JO - International Journal of Applied Mathematics and Computer Science
PY - 2005
VL - 15
IS - 1
SP - 73
EP - 88
AB - This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.
LA - eng
KW - uncertainty; positioning; mobile robots; multi-agent systems; action planning; vision sensors
UR - http://eudml.org/doc/207730
ER -

References

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  1. Adam A., Rivlin E. and Shimshoni I. (2001): Computing the sensory uncertainty field of a vision-based localization sensor. - IEEE Trans. Robot. Automat., Vol. 17, No. 3, pp. 258-267. 
  2. Ahuja R., Magnanti T. and Orlin J. (1993): Network Flows: Theory, Algorithms and Applications. - Englewood Cliffs: Prentice Hall. Zbl1201.90001
  3. Bączyk R. and Skrzypczyński P. (2001): Mobile robot localization by means of an overhead camera. - Proc. Conf. Automation 2001, Warsaw, Poland, pp. 220-229. 
  4. Bączyk R. (2001): Methods of correcting image distortions in alocalization system of a mobile robot. - Proc. 7-th Nat. Conf. Robotics, Wrocław, Poland, pp. 185-194. 
  5. Bączyk R., Kasiński A. and Skrzypczyński P. (2003): Vision-based mobilerobot localization with simple artificial landmarks. - Prep. 7th IFAC Symp. Robot Control, Wrocław, Poland, pp. 217-222. 
  6. Bączyk R. and Skrzypczyński P. (2003): A framework for vision-based positioningin a distributed robotic system. - Proc. Europ. Conf. Mobile Robots, Warsaw, Poland, pp. 153-158. 
  7. Brzykcy G., Martinek J., Meissner A. and Skrzypczyński P. (2001): Multi-agent blackboard architecture for a mobile robot. - Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, Maui, USA, pp. 2369-2374. Zbl1166.93353
  8. Castellanos J. and Tardòs J. (1999): Mobile Robot Localization and Map Building. A Multisensor Fusion Approach. - Dordrecht: Kluwer. 
  9. Coulouris G., Dollimore J. and Kindberg T. (1996): Distributed Systems. Concepts and Design. - Boston: Addison Wesley. Zbl0848.68021
  10. Crowley J. L. (1996): Mathematical foundations of navigation and perception for an autonomous mobile robot, In: Reasoning with Uncertainty in Robotics (L. Dorst, Ed.).- Berlin: Springer. 
  11. DeSouza G. and Kak A. C. (2002): Vision for mobile robot navigation: A survey.- IEEE Trans. Pattern Anal. Mach. Intell., Vol. 24, No. 2, pp. 237-267. 
  12. Feng L., Borenstein J. and Everett H. (1996): 'Where am I ?' Sensors and methods for autonomous mobile robot positioning. - Tech. Rep., Univ. of Michigan. 
  13. Haralick R. M. (1996): Propagating covariance in computer vision.- Int. J. Pattern Recog. Artif. Intell., Vol. 10, No. 5, pp. 561-572. 
  14. Heikkila J. (2000): Geometric camera calibration using circular control points.- IEEE Trans. Pattern Anal. Mach. Intell., Vol. 22, No. 10, pp. 1066-1077. 
  15. Ishiguro H. (1997): Distributed vision system: A perceptual information infrastructure for robot navigation. - Proc. Int. Joint Conf. Artif. Intell., Nagoya, Japan, pp. 36-43. 
  16. Jain R., Kasturi R. and Schunck B. (1995): Machine Vision. -Singapore: McGraw-Hill. 
  17. Kasiński A. and Bączyk R. (2001): Robust landmark recognition with application to navigation. - Proc. Conf. Computer Recognition Systems (KOSYR), Wrocław, Poland, pp. 401-407. 
  18. Kasiński A. and Hamdy A. (2003): Efficient illumination suppression in a sequence by motion detection combined with homomorphic filtering. -Proc. 27th Workshop AAPR Vision in a Dynamic World, Laxenburg, Austria, pp. 19-26. 
  19. Kasiński A. and Skrzypczyński P. (1998): Cooperative perception andworld-model maintenance in mobile navigation tasks, In: Distributed Autonomous Robotic Systems 3 (T. Luth et al., Eds.).- Berlin: Springer, pp. 173-182. 
  20. Kasiński A. and Skrzypczyński P. (2001): Perception network for the teamof indoor mobile robots.: Concept, architecture, implementation.- Eng. Appl. Artif. Intell., Vol. 14, No. 2, pp. 125-137. 
  21. Kasiński A. and Skrzypczyński P. (2002): Communication mechanism in a distributed system of mobile robots, In: Distributed Autonomous Robotic Systems 5 (H. Asama et al., Eds.). - Tokyo: Springer, pp. 51-60. 
  22. Kruse E., Gutsche R. and Wahl F. (1998): Intelligent mobile robot guidance intime varying environments by using a global monitoring system. - Proc. IFAC Symp. Intell. Autonomous Vehicles, Madrid, Spain, pp. 509-514. 
  23. Kuipers F. A., Korkmaz T., Krunz M. and Van Mieghem P. (2002): A review of constraint-based routing algorithms. - Tech. Rep., Delft Univ. Technol. 
  24. Lambert A. and Fraichard T. (2000): Landmark-based safe path planning for car-like robots. - IEEE Int. Conf. Robot. Automat., San Francisco, pp. 2046-2051. 
  25. Lazanas A. and Latombe J.-C. (1995): Motion planning with uncertainty: A landmark approach. - Artif. Intell., Vol. 76, No 1-2, pp. 287-317. Zbl0939.68863
  26. Lorenz D. and Raz D. (2001): A simple efficient approximation scheme for the restricted shortest path problem. - Oper. Res. Lett., Vol. 28, No. 5, pp. 213-219. Zbl0992.90057
  27. Latombe J.-C. (1991): Robot Motion Planning. - Dordrecht: Kluwer. 
  28. Miura J. and Shirai Y. (1993): An uncertainty model of stereo vision and its application to vision-motion planning of robot. - Proc. Int. Joint Conf. Artif. Intell., Chambery, France, pp. 1618-1623. 
  29. Moon I., Miura J. and Shirai Y. (1999): On-line viewpoint and motion planning for efficient visual navigation under uncertainty. - Robot. Autonom. Syst., Vol. 28, No 2, pp. 237-248. 
  30. Muller J. (1996): The Design of Intelligent Agents: A Layered Approach.- Berlin: Springer. 
  31. Shah S. and Aggarwal J. (1994): A simple calibration procedure for fish-eye(high distortion) lens camera. - IEEE Int. Conf. Robot. Automat., San Diego, pp. 3422-3427. 
  32. Skrzypczyński P. (2004a): A team of mobile robots and monitoring sensors - From concept to experiment. - Adv. Robot., Vol. 18, No. 6, pp. 583-610. 
  33. Skrzypczyński P. (2004b): Using sensor uncertainty models to optimize the robot positioning actions, In: Intelligent Autonomous Systems 8 (F. Groen et al., Eds.). - Amsterdam, IOS Press, pp. 299-308. 
  34. Smith R. and Cheeseman P. (1987): On the estimation and representation of spatial uncertainty. - Int. J. Robot. Res., Vol. 5, No. 4, pp. 56-68. 
  35. Smith R. G. (1980): The contract net protocol: High-level communication and control in a distributed problem solver. - IEEE Trans. Comput., Vol. 29, No. 12, pp. 1104-1113. 
  36. Sysło M. M., Deo N. and Kowalik J. S. (1983): Discrete Optimization Algorithms with Pascal Programs. - Englewood Cliffs: Prentice-Hall. Zbl0574.90057
  37. Takahashi O. and Schilling R. J. (1989): Motion planning in a plane using generalized Voronoi diagrams. - IEEE Trans. Robot. Automat., Vol. 5, No. 2, pp. 143-150. 
  38. Takeda H., Facchinetti C. and Latombe J.-C. (1994): Planning the motions of a mobile robot in a sensory uncertainty field. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 16, No. 10, pp. 1002-1017. 

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