JACIII Vol.12 No.6 pp. 488-493
doi: 10.20965/jaciii.2008.p0488


Position Uncertainty Reduction of Mobile Robot Based on DINDs in Intelligent Space

TaeSeok Jin* and Hideki Hashimoto**

*Dept. of Mechatronics eng, DongSeo University, Churye 2dong, Sasang-Gu, Korea

**IIS, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

June 10, 2008
August 21, 2008
November 20, 2008
mobile robot, tracking, intelligent space, distributed sensors, uncertainty

This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace). This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a-priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot.

Cite this article as:
TaeSeok Jin and Hideki Hashimoto, “Position Uncertainty Reduction of Mobile Robot Based on DINDs in Intelligent Space,” J. Adv. Comput. Intell. Intell. Inform., Vol.12, No.6, pp. 488-493, 2008.
Data files:

    [1] L. Moreno and E. Dapena, “Path quality measure for sensor-based motion planning,” Robotics and Autonomous Systems, Vol.44, pp. 131-150, 2003.
    [2] B. Bouilly and T. Siméon, “A sensor-based motion planner for mobile robot navigation with uncertainty,” in Proc. of the Int. Workshop on RUR'95, Springer, Berlin, 1996, pp. 235-247.
    [3] M. Betke and L. Gurvits, “Mobile Robot Localization Using Landmarks,” Proc. of the IEEE/RSJ/GI Int. Conf. on Intelligent Robots and Systems, 1994, pp. 135-142.
    [4] D. J. Kriegman, E. Triendl, and T. O. Binford, “Stereo vision and navigation in buildings for mobile robots,” IEEE Trans. Robotics and Automation, Vol.5, No.6, pp. 792-803, 1989.
    [5] J.-H. Lee, G. Appenzeller, and H. Hashimoto, “An agent for intelligent spaces: Functions and roles of mobile robots in sensored, networked, thinking spaces,” in Proc. IEEE Conf. Intelligent Transportation Systems, Boston, MA, 1997, pp. 983-988.
    [6] Y. Nakamura, “Advanced Robotics: Redundancy and Optimization,” Addison-Wesley, 1991.
    [7] R. M. Haralick and L. G. Shapiro, “Computer and Robot Vision,” Addison-Wesley, 1993.
    [8] 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.
    [9] R. E. Kalman, “New Approach to Linear Filtering and Prediction Problems,” Trans. ASME, J. Basic Eng., Series 82D, pp. 35-45, Mar. 1960.
    [10] H. W. Sorenson, “Kalman Filtering Techniques,” Advances in Control Systems Theory and Applications, Vol.3, pp. 219-292, 1966.
    [11] M. Y. Han, B. K. Kim, K. H. Kim, and J. M. Lee, “Active Calibration of the Robot/Camera Pose Using the Circular Objects,” in Korean, Transactions on Control, Automation and Systems Engineering, Vol.5, No.3, pp. 314-323, Apr. 1999.
    [12] T. Akiyama, J.-H. Lee, and H. Hashimoto, “Evaluation of CCD camera arrangement for positioning system in intelligent space,” in Proc. Seventh Int. Symp. Artificial Life and Robotics (AROB'02), 2002, pp. 310-315.
    [13] A. Adam, E. Rivlin, and I. Shimshoni, “Computing the Sensory Uncertainty Field of a Vision-based Localization Sensor,” Proc. of the 2000 IEEE Int. Conf. on Robotics & Automation, Apr. 2000, pp. 2993-2999.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 05, 2021