Affiliation:
1. Department of Mechanical Engineering, Chongqing Three Gorges University, Chongqing 404100, China
Abstract
The study of path-planning algorithms is crucial for an electric logistics vehicle to reach its target point quickly and safely. In light of this, this work suggests a novel path-planning technique based on the improved A-star (A*) fusion dynamic window approach (DWA). First, compared to the A* algorithm, the upgraded A* algorithm not only avoids the obstruction border but also removes unnecessary nodes and minimizes turning angles. Then, the DWA algorithm is fused with the enhanced A* algorithm to achieve dynamic obstacle avoidance. In addition to RVIZ of ROS, MATLAB simulates and verifies the upgraded A* algorithm and the A* fused DWA. The MATLAB simulation results demonstrate that the approach based on the enhanced A* algorithm combined with DWA not only shortens the path by 4.56% when compared to the A* algorithm but also smooths the path and has dynamic obstacle-avoidance capabilities. The path length is cut by 8.99% and the search time is cut by 16.26% when compared to the DWA. The findings demonstrate that the enhanced method in this study successfully addresses the issues that the A* algorithm’s path is not smooth, dynamic obstacle avoidance cannot be performed, and DWA cannot be both globally optimal.
Funder
General project of Natural Science Foundation of Chongqing Science and Technology Commission
Science and Technology Research Program of Chongqing Municipal Education Commission
Reference27 articles.
1. A Review of Reinforcement Learning-Based Path Planning Methods for Self-Driving Cars;Xu;Appl. Res. Comput.,2023
2. Improved Ant Colony Algorithm for Adaptive Probabilistic Selection Model;Zheng;Autom. Technol. Appl.,2021
3. Sathyamoorthy, A., Liang, J., Patel, U., Guan, T., Chandra, R., and Manocha, D. (August, January 31). DenseCAvoid: Real-time Navigation in Dense Crowds using Anticipatory Behaviors. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.
4. Mobile Robot Motion Framework Based on Enhanced Robust Panel Method;Jasmin;Int. J. Control Autom. Syst.,2020
5. Global Dynamic Path Planning Incorporating Improved A* Algorithm and Dynamic Windowing Method;Cheng;J. Xi’An Jiaotong Univ.,2017
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