一种子目标和水平集方法融合的AUV动态航路规划新算法

针对当前水下避障航路规划算法中障碍物模型偏理想化，易导致不能安全避障，且算法规划速度偏慢的难题，提出了一种基于子目标法和水平集方法的自主实时航路规划算法.算法基于AUV的前视声呐探测的障碍物部分轮廓信息，预估障碍物尺寸和中心位置，据此得出安全可靠的子目标点，再通过滚动的子目标法实现完全避障，通过水平集方法提升规划速度.仿真结果表明，提出的算法均能做到100%的避障，且避障后的航路性能质量比预先规划的全局最优航路的性能质量下降得很小:航路长度和航行时间的平均增加量均不超过5%. 

A Novel Algorithm for Autonomous Real-Time Route Planning ofAUV Based on Sub-Target and Level Set Method

To solve the unsafe obstacle avoidance and low planning efficiency problems resulted from the more idealized obstacle model of the current underwater obstacle avoidance route planning algorithm, an autonomous real-time route planning algorithm based on the sub-object method and level set method was proposed. Based on the partial contour information of obstacles detected by AUV(autonomous underwater vehicle) forward-looking sonar, the algorithm was arranged to estimate the size and center position of obstacles in stages, and then to obtain safe and reliable sub target points. And then, a rolling sub target method was used to realize complete obstacle avoidance and a level set method was used to improve the planning speed. The simulation results show that the novel algorithm can achieve 100% obstacle avoidance, and the performance quality of the route after obstacle avoidance appears a little debased than that of the global optimal route obtained by the level set method:the average increase of route length and sailing time are less than 5%.