论文标题
具有静态多边形约束的最佳基于模型的轨迹计划
Optimal model-based trajectory planning with static polygonal constraints
论文作者
论文摘要
本文的主要贡献是一种针对受多边形约束的动力系统进行全球最佳轨迹的新方法。提出的方法是一种混合轨迹计划方法，它结合了图形搜索，即一种离散的路线图方法，即凸优化，即完整的路径方法。与过去的方法相反，这些方法的重点是使用简单的障碍物近似或亚最佳空间离散化，我们的方法能够使用多边形约束的确切几何形状，以计划最佳轨迹。通过计划DUBINS CAR模型的距离 - 最佳轨迹以及海洋车辆的时间，距离和能量最佳轨迹，通过模拟评估所提出方法的性能和灵活性。
The main contribution of this paper is a novel method for planning globally optimal trajectories for dynamical systems subject to polygonal constraints. The proposed method is a hybrid trajectory planning approach, which combines graph search, i.e. a discrete roadmap method, with convex optimization, i.e. a complete path method. Contrary to past approaches, which have focused on using simple obstacle approximations, or sub-optimal spatial discretizations, our approach is able to use the exact geometry of polygonal constraints in order to plan optimal trajectories. The performance and flexibility of the proposed method is evaluated via simulations by planning distance-optimal trajectories for a Dubins car model, as well as time-, distance- and energy-optimal trajectories for a marine vehicle.
