An AUV localization and path planning algorithm for terrain-aided navigation. (August 2020) - Teng, Ma; Ye, Li; Yuxin, Zhao; Yanqing, Jiang; Zheng, Cong; Qiang, Zhang; Shuo, Xu
Abstract: Terrain-aided navigation (TAN) holds high potential for long-term accurate navigation of autonomous underwater vehicles (AUVs), and path planning algorithms are essential in TAN to decrease positioning errors by avoiding flat areas. This study proposed an AUV localization and path planning algorithm for TAN, which consists of a value function calculation and online path planning. In the value function calculation, the topographic complexity is treated as a factor that influences AUV state transition probabilities to calculate the optimal policy; meanwhile, the online path planning applies a particle filter to localize and command AUVs, and particle weights are calculated according to topographic complexity. Simulation experimental results demonstrate that this algorithm could provide paths with accurate TAN location results and good maneuvering performance. Highlights: Take terrain complexity as the state transfer probability in the online path planning. Propose the particle initialization method considering terrain complexity and similarity. Propose the online path planning method considering vehicle motion uncertainty and real-time position estimation.