UAV flight strategy algorithm based on dynamic programming

Unmanned aerial vehicles (UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV's action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming (DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm. Based on the analysis of DP, this paper proposes a hierarchical directional DP (DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.