This paper presents methods for dramatically improving the performance of sampling-based kinodynamic planners. The key component is the first-known complete, exact steering method that produces a time-optimal trajectory between any states for a vector of synchronized double integrators. This method is applied in three ways: 1) to generate RRT edges that quickly solve the two-point boundary-value problems, 2) to produce a (quasi)metric for more accurate Voronoi bias in RRTs, and 3) to iteratively time-optimize a given collision-free trajectory. Experiments are performed for state spaces with up to 2000 dimensions, resulting in improved computed trajectories and orders of magnitude computation time improvements over using ordinary metrics and constant controls.

翻译：本文提出了显著提升基于采样的运动动力学规划器性能的方法。核心组件是首个已知的完整、精确的导向方法，该方法能为同步双积分器状态向量生成任意两状态间的时间最优轨迹。该方法通过三种方式应用：1）生成RRT边以快速求解两点边值问题；2）生成（拟）度量以实现更精确的RRT Voronoi偏置；3）对给定无碰撞轨迹进行迭代时间优化。实验在高达2000维的状态空间中进行，结果表明，与使用普通度量和恒定控制相比，计算轨迹得到改善，计算时间提升数个数量级。