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| Received:April 28, 2003Revised:August 25, 2004 |
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| Local minima-free design of artificial coordinating fields |
| XingjianJING, Yuechao WANG |
| (Robotics Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang Liaoning 110016, China; The Graduate School of Chinese Academy of Sciences, Beijing 100083, China) |
| Abstract: |
| In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF. |
| Key words: Artificial coordinating field (ACF) Artificial potential field Local minima Dynamic uncertain environment Robot |
