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Two New Methods for Path Planning of Autonomous Mobile Robot

Author Affiliations

  • 1Department of New Sciences and Technologies, University of Tehran, Tehran, IRAN
  • 2 Department of Computer and Electrical Engineering, University of Tehran, Tehran, IRAN
  • 3 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, IRAN
  • 4 Department of Electrical Engineering, Sharif University of Technology, Tehran, IRAN

Res. J. Recent Sci., Volume 3, Issue (5), Pages 110-115, May,2 (2014)


This paper investigates four methods for finding shortest path between source and destination in a specific environment. For the known gradient method, we have propped a way to reduce the computational complexity of gradient field. Besides, the proposed method attempts to find the optimal path starting from a suboptimal path with the lowest computations. The considered robot is a mobile robot with three freedom degrees in two-dimensional environment. This will cause the isolation of the angle of trajectory path. The result of the simulations of the methods shows that the new approach provides an appropriate method for mobile robot routing in comparison to other methods.


  1. Jan K., Chang G.Y. and Parberry I., Optimal path planning for mobile robot navigation, IEEE/ASME Trans. Mechatronics, (13), 451 ( 2008)
  2. Tae-Kyeong Lee, Sang-HoonBaeka, Young-Ho Choi and Se-Young Oh,Smooth coverage path planning and control of mobile robots based on high-resolution grid map representation, Robotics and Autonomous Systems, (59), 801812 (2011)
  3. Boult T.E., Dynamic digital distance maps in two dimensions, IEEE Trans. Robot, (6), 590597 (1990)
  4. Subbarao K. and Larry S.D., Multiresolution path planning for mobile robots, IEEE J. Robot, (2), 135145 (1986)
  5. Alexopoulos C. and Griffin P.M., Path planning for a mobile robot, IEEE Trans. Syst., Man, Cybern, 22), 318322 (1992)
  6. Zelinsky, A mobile robot exploration algorithm, IEEE Trans. Robot, (8), 707717 (1992)
  7. Zheng T.G., Huan H, Aaron S, Ant Colony System ALgorithm for Real Time Globally Optimal Path Planing of Mobile Robots, ACTA Automatic Sinica, (33), 279-285 (2007)
  8. S.SGe, Y.J Cui, New potential functions for mobile robot path planning, IEEE Transactions on Robotics and Automation, (16), 615-620 (2000)
  9. Li L, Ye T, Tan M. Present state and future development of mobile robot technology research, Conf.Robot, 475480, (2002)
  10. V. Boschian, A. Pruski, Grid modeling of robot cells: a memory-effcient approach, Journal of Intelligent and Robotic Systems, (8), 201-223 (1993)
  11. Murphy R.R., Hughes K., Marzilli A. and Noll E., Integrating explicit path planning with reactive control of mobile robots using trulla, Robotics and Autonomous Systems, (27), 225-245 (1999)
  12. Barraquand J., Langlois B. and Latombe J.C., Numerical potential field techniques for robot path planning,IEEE Trans. Syst., Man, Cybern., (22), 224241(1992)
  13. Yang X., Moallem M. and Patel R.V., A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation,IEEE Trans. Syst., Man, Cybern. B, Cybern., (35), 12141224 (2005)
  14. Jiang K., Seneviratne L.D. and Earles S.W. E., Shortest path based path planning algorithm for nonholonomic mobile robots, J. Intell. Robot. Syst., Theory Appl., (24), 347366 (1999)
  15. Gabriely Y. and Rimon E., Competitive On-line Coverage of Grid Environments by a Mobile Robot, Computational Geometry, (24), 197-224 (2003)
  16. Hu T.C., Kahng A.B. and Robins G., Optimal robust path planning in general environments, IEEE Trans. Robot. Autom., (9), 775784 (1993)
  17. Laumond J.P., Jacobs P.E., Taix M. and Murray R.M., A motion planner for nonholonomic mobile robots, IEEE Trans. Robot. Autom., (10), 577593 (1994)
  18. Sharifi M. and Shahriari B., Pareto Optimization of Vehicle Suspension Vibration for a Nonlinear Half-car Model Using a Multi-objective Genetic Algorithm, Research Journal of Recent Sciences, 1(8), 17-22 (2012)
  19. Panah Amir, Enhanced SLAM for a Mobile Robot using Unscented Kalman Filter and Radial Basis Function Neural Network, Research Journal of Recent Sciences, 2(2), 69-75 (2013)
  20. Mark W. Spong, S. Hutchinson, M. Vidyasagar, Robot Modeling and Control, John Wiley and Sons, Inc., (2005)
  21. Pamosoaji A.K. and Hong K., A Path-Planning Algorithm Using Vector Potential Functions in Triangular Regions, IEEE Trans. Systems, Man, and Cybernetics: Systems, (43), 832-842 (2013)