.png){kind=icon}
返回
Directed Explorations During Flood Disasters Using Multi-UAV System
.png){kind=icon}
PRE
AI
DOI：10.1109/CASE49997.2022.9926454.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The disaster relief operations during floods require time critical information of the flooded area to save lives. Finding critical regions of the disaster struck area in a limited time frame is crucial for effective relief planning. In this paper, we propose a multi-UAV based system with directed explorations of flooded area to gather time-critical ground information using deep reinforcement learning based controls. We learn an exploration policy for the multi-UAV system with limited battery for autonomous coverage of the flooded region. Further, we integrate D8 flow algorithm that approximates the water flow direction based on image pixel information of a sub-region in the UAVs' exploration strategy. The results show that our proposed method for multi-UAV exploration of flooded area outperforms other methods from the literature. Moreover, the learnt multi-UAV exploration policy is able to generalize to unseen flooded regions without any retraining.
期刊
I
IF:
0
论文数:
16
被引数:
0
机构
引用论文
Analysis of Hydrograph Shape Affected by Flow-Direction Assumptions in Rainfall-Runoff Models.png)
WATER
OAAI
WATERIF3
OAAI分享收藏A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms使用经典和启发式算法对机器人技术中的覆盖路径规划进行全面审查IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容