Volume 50 Issue 2
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GONG H,NI C,WANG P,et al. A smooth path planning method based on Dijkstra algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(2):535-541 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0377
Citation: GONG H,NI C,WANG P,et al. A smooth path planning method based on Dijkstra algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(2):535-541 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0377

A smooth path planning method based on Dijkstra algorithm

doi: 10.13700/j.bh.1001-5965.2022.0377
Funds:  China Postdoctoral Science Foundation (2021M702030); Science and Technology Plan Project of Transportation Department of Shandong (2021B120)
More Information
  • Corresponding author: E-mail:1149993471@qq.com
  • Received Date: 18 May 2022
  • Accepted Date: 23 Jun 2022
  • Available Online: 31 Oct 2022
  • Publish Date: 15 Sep 2022
  • When the mobile robot moves along the path planned by the Dijkstra algorithm in a complex environment, due to the planned path having many turning points and some turning angles being small, the mobile robot has to turn frequently or even pause to complete the turning, which seriously affects the working efficiency of the robot. In this study, the mobile robot’s actual scene data is combined with the geometric topology method to propose smooth path planning method based on Dijkstra algorithm. The continuous map is obtained according to the application scenario, and the discrete lattice is randomly generated after the discretization of the continuous map, and the Euclidean distance between the points is calculated. Multiple points which are close to the discrete points and whose connection does not cross the barrier are selected to connect them and generate the discrete graph. The Dijkstra algorithm is used to search the optimal path as the guidance path in the discrete graph. The geometric topology is utilized to determine the optimum action and the running path that the mobile robot should follow at each time as it proceeds along the guidance path in conjunction with the actual scene information. Experimental results show that the proposed method can effectively reduce the cumulative turning angles, increase the minimum average turning angle, and improve the smoothness of the planned path, thus shortening the movement time of the mobile robot and improving the working efficiency of the robot.

     

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