Cooperative Local Path Planning for Multi-unmanned Vehicles Formation Using the Enhanced Artificial Potential Field
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1103-1_34
Reference20 articles.
1. Hanli, Y., Qiliang, L., Weizhen, Z.: Robot obstacle avoidance based on improved artificial potential field method. In: 2021 International Conference on Control, Automation and Information Sciences (ICCAIS), pp. 769–775. IEEE (2021). https://doi.org/10.1109/iccais52680.2021.9624644
2. Qin, H., Shao, S., Wang, T., Yu, X., Jiang, Y., Cao, Z.: Review of autonomous path planning algorithms for mobile robots. Drones 7(3), 211 (2023). https://doi.org/10.3390/drones7030211
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4. Sezer, V., Gokasan, M.: A novel obstacle avoidance algorithm: “follow the gap method”. RRobot. Auton. Syst. 60(9), 1123–1134 (2012). https://doi.org/10.1016/j.robot.2012.05.021
5. Fan, X., Guo, Y., Liu, H., Wei, B., Lyu, W.: Improved artificial potential field method applied for auv path planning. Math. Probl. Eng. 2020, 1–21 (2020). https://doi.org/10.1155/2020/6523158
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