提出新路径规划方法,让无人舰艇更好避障,尤其擅长绕行移动目标。
Path planning for unmanned naval surface vehicles
- 融合三种路径算法,全局规划更高效
- 局部规划能判断障碍物方向,主动绕后而非并行
- 仿真验证优于传统D*算法,适合动态水域航行
目前针对无人水面舰艇(USVs)的实时固定障碍物避障已有多种方法,但对移动障碍物(如船只、游泳者、其他USVs)的避障仍具挑战。本文提出全新解决方案:结合全局路径规划器(基于已知固定障碍物,规划起点到终点路径)与局部路径规划器(应对移动障碍物及未知固定障碍物)。全局规划器创新性地融合三种算法:经典Grassfire、改进版Grassfire及新型概率路网(Probabilistic Roadmap)变体;局部规划器则基于障碍物运动方向与全局路径的关系,做出更高层次决策,使USV系统性绕至障碍物后方,而非长期并行等待通过。仿真验证了该方法的有效性,并与经典的D*算法进行对比,讨论了其他动态路径规划系统,指出其通常不主动绕后。结果表明,本方法在复杂动态环境中更具优势。
原文摘要 · Abstract (English)
There nowadays is a myriad of approaches to real-time avoidance of fixed obstacles for unmanned surface vehicles (USVs) and, to a lesser extent, also the task of avoiding moving obstacles such as boats, ships, swimmers, and other USVs, but both topics still present challenges. This paper offers novel approaches to both of these problems. It uses a combination of a global path planner, which finds a path from a start point to a goal point that avoids fixed obstacles (given that their locations are known in advance), and a local path planner, which can circumnavigate a moving obstacle (as well as any previously unknown fixed obstacles). The global planner is novel in that it employs a combination of three path planners, one known in the literature as Grassfire, one that is a new modification of Grassfire, and one that is a new, and arguably more intuitive, version of the well-known Probabilistic Roadmap. The local planner is novel in that it employs a higher-level decision logic based on its observations regarding the direction of movement of the obstacle relative to the USVs global path. This logic enables the USV to determine the best strategy for avoiding the obstacle by systematically routing the vehicle behind the obstacle rather than running parallel to it until the opportunity to pass appears. Simulations are provided that validate these claims. For comparison with other systems, the simulations include an implementation of the well-known D* algorithm, and the discussion covers additional dynamic path planning systems, which, like D*, do not necessarily route the vehicle behind the moving obstacle.
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