Path Planning for UAV with Constrained conditions Based on Ant Colony Algorithm
Huiming Zhang, Yi Lu, Haizhen Zhu, Zhonghui Xiao, Chunqing Gao
Available Online May 2017.
- https://doi.org/10.2991/icmeit-17.2017.91How to use a DOI?
- UAV; constrained conditions; ant colony algorithm; path planning.
- In order to improve UAV's operational efficiency and survival probability, the optimal path of an UAV should be designed before the UAV performs a mission. This paper applies UAV's constrained conditions to the search strategies of ant colony and use a new evaluation method of path's cost. The algorithm's state transformation rules and pheromone updating rules are improved. These make its convergence speed and global searching ability enhanced remarkably. The simulation results show that this method can get a flight path which can avoid threats effectively in a short time and is a more efficient path planning method
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Huiming Zhang AU - Yi Lu AU - Haizhen Zhu AU - Zhonghui Xiao AU - Chunqing Gao PY - 2017/05 DA - 2017/05 TI - Path Planning for UAV with Constrained conditions Based on Ant Colony Algorithm BT - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017) PB - Atlantis Press SP - 475 EP - 482 SN - 2352-538X UR - https://doi.org/10.2991/icmeit-17.2017.91 DO - https://doi.org/10.2991/icmeit-17.2017.91 ID - Zhang2017/05 ER -