Cooperative target searching and tracking via UCT with probability distribution model

Ruoxi Qin (1) , Tian Wang (1) , Haotian Jiang (1) , Qianhong Yan (1) , Weikang Wang (1) , Hichem Snoussi (2)

1 School of Automation and Electrical Engineering [Beijing] (University of Science and Technology Beijing)
2 LM2S - Laboratoire Modélisation et Sûreté des Systèmes

As Unmanned Aerial Vehicle's (UAV) battery life and stability develop, multiple UAVs are having more and more applications in the uninterrupted patrol and security. Thus UAV's searching, tracking and trajectory planning become important issues. This paper proposes an online distributed algorithm used in UAV's tracking and searching, with the consideration of UAV's practical need to recharge under limited power. We propose a Quantum Probability Model to describe the partially observable target positions, and we use Upper Confidence Tree (UCT) algorithm to find out the best searching and tracking route based on this model. We also introduce the Teammate Learning Model to handle the nonstationary problems in distributed reinforcement learning.

Domains: Signal and Image processing

Ruoxi Qin, Tian Wang, Haotian Jiang, Qianhong Yan, Weikang Wang, et al.. Cooperative target searching and tracking via UCT with probability distribution model. 2016 IEEE International Conference on Digital Signal Processing (DSP), Oct 2016, Beijing, China. pp.560-564, ⟨10.1109/ICDSP.2016.7868620⟩. ⟨hal-02307416⟩