Decision Modeling of UAV On-Line Path Planning Based on IMM

Abstract

In order to enhance the capability of tracking targets autonomously of UAV, a model for UAV on-line path planning is established based on the theoretical framework of partially observable markov decision process(POMDP). The elements of the POMDP model are analyzed and described. According to the diversity of the target motion in real world, the law of state transition in POMDP model is described by the method of Interactive Multiple Model(IMM) To adapt to the target maneuvering changes. The action strategy of the UAV is calculated through nominal belief-state optimization(NBO) algorithm which is designed to search optimal action policy to minimize the cumulative cost of action. The generated action strategy controls the UAV flight. The simulation results show that the established POMDP model can achieve autonomous planning for UAV route, and it can control the UAV to effectively track target. The planning path is more reasonable and efficient than the result of using single state transition law.

Robust optimization of consistency in filling of rib-grooves for titanium alloy multi-rib eigenstructure

“…(5) The material flow in the rib-grooves is basically unaffected by the temperature change. Gao et al [33] compared the material flow in the rib-grooves at different temperatures and showed that the relationship between temperature and material flow in the rib-grooves is not significant. 𝜌 =SSI/SST (5) where SSI is the sum of squared deviations of the Ith uncertainty factor (I=1, 2, 3, 4); SST is the total sum of squared deviations.…”