Teng Ma, Ye Li, Yuxin Zhao, Yanqing Jiang, Zheng Cong, Qiang Zhang, Shuo Xu
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China.
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China.
ISA Trans. 2020 Aug;103:215-227. doi: 10.1016/j.isatra.2020.04.007. Epub 2020 Apr 23.
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.
地形辅助导航（TAN）在自主水下航行器（AUV）的长期精确导航方面具有巨大潜力，并且路径规划算法在TAN中对于通过避开平坦区域来减少定位误差至关重要。本研究提出了一种用于TAN的AUV定位和路径规划算法，该算法由价值函数计算和在线路径规划组成。在价值函数计算中，将地形复杂性视为影响AUV状态转移概率的一个因素来计算最优策略；同时，在线路径规划应用粒子滤波器对AUV进行定位和指挥，并根据地形复杂性计算粒子权重。仿真实验结果表明，该算法能够提供具有精确TAN定位结果和良好机动性能的路径。
