Improved ant colony algorithm for global path planning-Reference-Cited by-同舟云学术

Improved ant colony algorithm for global path planning

Published:2017 Issue: Volume: Page:
ISSN:0094-243X
Container-title:AIP Conference Proceedings
language:
Short-container-title:

Author:

Li Pengfei,Wang Hongbo,Li Xiaogang

Publisher

Author(s)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.4977369

Reference10 articles.

1. Masoud Nosrati*. Investigation of the * (Star) Search Algorithms: Characteristics, Methods and Approaches. World Applied Programming, Vol. 2, No. 4, April 2012, pp. 251–256.

2. Jennings A L, Ordonez R, Ceccarelli N. Dynamic programming applied to UAV way point path planning in wind. Proceedings of the IEEE International Symposium, September 2008, pp. 215–220.

3. A note on two problems in connexion with graphs

4. T. P. Fries. Fuzzy genetic motion planning under diverse terrain conditions for autonomous robots. Proceedings of the Second IASTED International Conference on Circuits, Signals, and Systems, January 2004. 504–508.

5. K. Althoefer. Neuro-fuzzy motion planning for robotic manipulators. Ph.D. thesis, King’s College, London. 1997.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review of Path Planning Methods for Marine Autonomous Surface Vehicles;Journal of Marine Science and Engineering;2024-05-16

2. Research on Obstacle Avoidance Method for Unmanned Clusters Based on Artificial Potential Field;2023 2nd International Conference on Artificial Intelligence and Computer Information Technology (AICIT);2023-09-15

3. A Method of UAV Formation Transformation Based on Reinforcement Learning Multi-agent;Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications;2022

4. A Mobile Service Robot Global Path Planning Method Based on Ant Colony Optimization and Fuzzy Control;Applied Sciences;2021-04-16