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http://dx.doi.org/10.5391/JKIIS.2004.14.4.438

Position Estimation of Autonomous Mobile Robot Using Geometric Information of a Moving Object  

Jin, Tae-Seok (동경대학 생산기술연구소)
Lee, Jang-Myung (부산대학교 전자공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.14, no.4, 2004 , pp. 438-444 More about this Journal
Abstract
The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.
Keywords
이동로봇;자기위치추정;카메라센서;이동물체;칼만필터;
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  • Reference
1 R. A. Brooks, "A Robust Layered Control System for a Mobile Robot," IEEE J. of Robotics and Automation, vol. RA-2, no. 1, pp.14-23, April, 1986.
2 T. S. Jin, J. M. Lee, "Pose determination of a mobile-task robot using an active calibration scheme," Industrial Electronics, Proceedings of the 2002 IEEE International Symposium on, vol. 2, pp. 447-452, 2002.
3 John J. Leonard and Hugh F, Durrant-Whyte, "Mobile Robot Localization by Tracking Geometric Beacons," IEEE Trans. Robotics and Automation, vol. 7, no.3, pp. 376~382, 1991.   DOI   ScienceOn
4 M. Betke et al., "Mobile Robot Localization Using Landmarks," Proc. of the IEEE/ RSJ/GI Int. Conf. on Intelligent Robots and Systems, pp. 135~142, 1994.
5 J. David, Kreigman et al., "Stereo vision and navigation in buildings for mobile robots," IEEE Trans. Robotics and Automation, vol. 5, no. 6, pp. 792~803, 1989.   DOI   ScienceOn
6 K. Komoriya, E. Oyama and K. Tani, "Planning of Landmark Measurement for the Navigation of a Mobile Robot," Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1476–1481, 1992.
7 Y. Nakamura, Advanced Robotics : Redundancy and Optimization, Addison-Wesley, 1991.
8 Robert M. Haralick and Linda G. Shapiro, Computer and Robot Vision, Addison-Wesley, 1993.
9 N. Ayache and O. D. Faugeras, "Maintaining Representations of the Environment of a Mobile Robot", IEEE Trans. Robotics and Automation, vol. 5, no. 6, Dec, 1989.
10 R. E. Kalman, "A New Approach to Linear Filtering and Prediction Problems," Trans, ASME, J. Basic Eng, Series 82D, pp. 35-45, Mar. 1960.
11 H. W. Sorenson, "Kalman Filtering Techniques," Advances in Control Systems Theory and Applications, vol. 3, pp. 219-292, 1966.
12 R. Talluri,J. K. Aggarwal, "Position estimation for an autonomous mobile robot in an outdoor environment," Robotics and Automation, IEEE Transactions on, vol. 8, no.5, pp. 573-584, 1992.   DOI   ScienceOn