实时避障并利用海流，让无人船快速安全抵达目标
SMART-OC: A Real-time Time-risk Optimal Replanning Algorithm for Dynamic Obstacles and Spatio-temporally Varying Currents
- 基于动态障碍与海流变化，构建时间-风险最优路径规划模型
- 仿真中无人船能快速重规划路径，避开障碍并利用海流节省时间
- 适合复杂海洋环境下的无人船实时导航，尤其关注安全性与效率
典型海洋环境具有时空变化的海流和动态障碍，对无人水面艇（USVs）的安全高效导航构成重大挑战。因此，USVs需基于实时信息持续调整路径，以避免碰撞并利用海流沿阻力最小路径抵达目标。为此，本文提出一种新算法——自适应形态重构树用于动态障碍与海流（SMART-OC），实现动态环境下的实时时间-风险最优重规划。SMART-OC将路径上的障碍物风险与到达目标的时间成本结合，寻找时间-风险最优路径。仿真实验验证了该算法的有效性：无人船能快速重规划路径，成功避开动态障碍，并有效利用海流抵达目标。
原文摘要 · Abstract (English)
Typical marine environments are highly complex with spatio-temporally varying currents and dynamic obstacles, presenting significant challenges to Unmanned Surface Vehicles (USVs) for safe and efficient navigation. Thus, the USVs need to continuously adapt their paths with real-time information to avoid collisions and follow the path of least resistance to the goal via exploiting ocean currents. In this regard, we introduce a novel algorithm, called Self-Morphing Adaptive Replanning Tree for dynamic Obstacles and Currents (SMART-OC), that facilitates real-time time-risk optimal replanning in dynamic environments. SMART-OC integrates the obstacle risks along a path with the time cost to reach the goal to find the time-risk optimal path. The effectiveness of SMART-OC is validated by simulation experiments, which demonstrate that the USV performs fast replannings to avoid dynamic obstacles and exploit ocean currents to successfully reach the goal.
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