Q(λ) Based Vector Direction for Path Planning Problem of Autonomous Mobile Robots

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)

Abstract

This paper presents a novel algorithm to improve the efficiency of path planning for autonomous mobile robots. In an obstacle-free environment, the path planning of a robot is attained by following the vector direction from its current position to the goal position. In an obstacle environment, while following the vector direction, a robot has to avoid obstacles by rotating the moving direction. To accomplish the obstacle avoidance task for the mobile robot, the Q(λ) algorithm is employed to train the robot to learn suitable moving directions. Experimental results show that the proposed algorithm is soundness and completeness with a fast learning rate in the large environment of states and obstacles.

Keywords

Reinforcement learning Q-learning Q(λ) algorithm Path planning Mobile robots 

Notes

Acknowledgments

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2010-0012609).

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Hyun Ju Hwang
    • 1
  • Hoang Huu Viet
    • 1
  • TaeChoong Chung
    • 1
  1. 1.Artificial Intelligence Lab, Department of Computer Engineering, School of Electronics and InformationKyung Hee UniversityYonginSouth Korea

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