We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Trans-UTPA: PSO and MADDPG based multi-UAVs trajectory planning algorithm for emergency communication.
- Authors
Jie Li; Shuang Cao; Xianjie Liu; Ruiyun Yu; Xingwei Wang
- Abstract
Communication infrastructure is damaged by disasters and it is difficult to support communication services in affected areas. UAVs play an important role in the emergency communication system. Due to the limited airborne energy of a UAV, it is a critical technical issue to effiectively design flight routes to complete rescue missions. We fully consider the distribution of the rescue area, the type of mission, and the flight characteristics of the UAV. Firstly, according to the distribution of the crowd, the PSO algorithm is used to cluster the target-POI of the task area, and the neural collaborative filtering algorithm is used to prioritize the target-POI. Then we also design a Trans-UTPA algorithm. Based on MAPPO 's policy network and value function, we introduce transformermodel tomake Trans-UTPA's policy learning have no action space limitation and can be multi-task parallel, which improves the efficiency and generalization of sample processing. In a three-dimensional space, the UAV selects the emergency task to be performed (data acquisition and networking communication) based on strategic learning of state information (location information, energy consumption information, etc.) and action information (horizontal flight, ascent, and descent), and then designs the UAV flight path based on the maximization of the global value function. The experimental results show that the performance of the Trans-UTPA algorithm is further improved compared with the USCTP algorithm in terms of the success rate of each UAV reaching the target position, the number of collisions, and the average reward of the algorithm. Among them, the average reward of the algorithm exceeds the USCTP algorithm by 13%, and the number of collisions is reduced by 60%. Compared with the heuristic algorithm, it can cover more target-POIs, and has less energy consumption than the heuristic algorithm.
- Subjects
EMERGENCY communication systems; EMERGENCY management; DRONE aircraft; HEURISTIC algorithms; COMMUNICATION infrastructure; ENERGY consumption
- Publication
Frontiers in Neurorobotics, 2023, Vol 17, p1
- ISSN
1662-5218
- Publication type
Article
- DOI
10.3389/fnbot.2022.1076338