Approximation of Optimal Moving Paths of Huge Robot Reclaimer with a 3D Range Finder

  • Kwan-Hee Lee
  • Hyo-Jung Bae
  • Sung-Je Hong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)


This paper proposes a simple method for approximating the optimal moving paths of a huge robot reclaimer located in the outdoor material stock yard with emphasis on safety, energy consumption, and transfer time. The reclaimer is equipped with a 3D range finder to measure the shape of material piles in the yard, and the material yard is modeled into 3D space where 2D section of grid type is constructed in several layers. To define a safety function against moving between grids, a simplified Voronoi diagram that has a minimized extension error of vertex is used. In addition, the function of energy consumption and transfer time required when the control point of the reclaimer moves between 3D grids is defined. This is used as a cost evaluation factor of path optimization along with the safety function. The proposed method can be readily applied to low-performance industrial control devices.


Control Point Path Planning Voronoi Diagram Curve Segment Range Finder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Canny, J., Donald, B.: Simplified Voronoi Diagrams. Discrete & Computational Geometry 3, 219–236 (1988)MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Bajaj, C., Kim, M.-S.: Algorithms for Planar Geometric Models. In: Lepistö, T., Salomaa, A. (eds.) ICALP 1988. LNCS, vol. 317, pp. 67–81. Springer, Heidelberg (1988)Google Scholar
  3. 3.
    Canny, J.: The Complexity of Robot Motion Planning, pp. 128–147. MIT press, Cambridge (1987)Google Scholar
  4. 4.
    Choi, C.-T., Lee, K.-H., Shin, K.-T., Hong, K.-S., Ahn, H.-S.: Automatic Landing Method of a Reclaimer on the Stockpile. IEEE Trans. on System, Man, and Cybernetics-Part C: Applications and Reviews 29(1), 308–314 (1999)CrossRefGoogle Scholar
  5. 5.
    Baase, S.: Computer Algorithms: Introduction to Design and Analysis, 2nd edn. (1988)Google Scholar
  6. 6.
    Walker, R.: Algebraic Curves. Springer, New York (1978)MATHGoogle Scholar
  7. 7.
    Lee, J.G., Chung, H.Y.: Global Path Planning for Mobile Robot with Grid-Type World Model. Robotics & Computer-Integrated Manuf. 11(1), 13–21 (1994)CrossRefGoogle Scholar
  8. 8.
    Chen, M., Zalzala, A.M.S.: A Genetic Approach to Motion Planning of Redundant Mobile Manipulator Systems Considering Safety and Configuration. Journal of Robotic Systems 14(7), 529–544 (1997)MATHCrossRefGoogle Scholar
  9. 9.
    Foskey, M., Garber, M., Lin, M.C., Manocha, D.: A Voronoi-Based Hybrid Motion Planner for Rigid Bodies. Intelligent Robotics and Systems 1, 55–60 (2001)Google Scholar
  10. 10.
    Takahashi, O., Schilling, R.J.: Motion Planning in a Plane Using Generalized Voronoi Diagrams. IEEE Trans. on Robotics and Automation 5(2) (April 1989)Google Scholar
  11. 11.
    Hoff, K., Culver, T., Keyser, J.: Interactive motion planning using hardware-accelerated computation of generalized Voronoi diagrams. In: Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2931–2937 (2000)Google Scholar
  12. 12.
    Suh, S.-H., Shin, K.G.: A variational dynamic programming approach to robot-path planning with a distance-safety criterion. IEEE Journal of Robotics and Automation 4(3), 334–349 (1988)CrossRefGoogle Scholar
  13. 13.
    Sun, K., Lumelsky, V.: Path planning among unknown obstacles: the case of a three-dimensional Cartesian arm. IEEE Trans. on Robotics and Automation, 776–786 (1992)Google Scholar
  14. 14.
    Alexander, R.S., Rowe, N.C.: Path Planning by Optimal-Path-Map Construction for Homogeneous-Cost Two-Dimensional Regions. In: IEEE Int. Conf. Robotics and Automation, pp. 1924–1929 (1990)Google Scholar
  15. 15.
    Lumelsky, V.J., Mukhopadhyay, S., Sun, K.: Dynamic Path Planning in Sensor-Based Terrain Acquisition. IEEE Trans. Robotics and Automation 6(4), 462–472 (1990)CrossRefGoogle Scholar
  16. 16.
    Lozano-Perez, T.: Spatial planning: A configuration space approach. IEEE Trans. Comput. C-32, 108–120 (1983)MATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Surmann, H., Nuechter, A., Hertzberg, J.: An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Robotics and Autonomous Systems, 181–198 (2003)Google Scholar
  18. 18.
    Miura, J., Negishi, Y., Shirai, Y.: Mobile Robot Map Generation by Integrating Omnidirectional Stereo and Laser Range Finder. In: Proceedings of 2002 IEEE/RSJ Int. Conf. on Intelligent Robotics and Systems, pp. 250–255 (2002)Google Scholar
  19. 19.
    Aboshosha, A., Zell, A.: Robust mapping and path planning for indoor robots based on sensor integration of sonar and a 2D laser range finder. In: IEEE 7th International Conference on Intelligent Engineering Systems (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kwan-Hee Lee
    • 1
  • Hyo-Jung Bae
    • 1
  • Sung-Je Hong
    • 2
  1. 1.Mechanical and Electrical Engineering TeamResearch Institute of Industrial Scnence & TechnologyRepublic of Korea
  2. 2.Dept. of Computer Science and EngineeringPohang University of Science and TechnologyRepublic of Korea

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