不依赖优化，用图搜索实时拼接轨迹段，实现高速安全导航。
STITCHER: Real-Time Trajectory Planning with Motion Primitive Search
- 用图搜索拼接短轨迹段生成长路径
- 毫秒级生成数十米长的安全轨迹
- 适合高实时性要求的自动驾驶场景
在大型复杂环境中实现自主高速导航，需实时生成动态可行、无碰撞且满足约束的敏捷轨迹。现有主流方法依赖数值优化以系统化计算高质量轨迹，但对计算时间的严格要求及数值不稳定性风险，限制了其在安全关键场景的应用。本文提出无需优化的规划框架STITCHER，通过图搜索将短轨迹段拼接成远距离路径，实现实时规划。该框架结合创新架构与多项算法改进，显著优于现代优化类规划器。仿真结果表明，可在毫秒级生成覆盖数十米的无障碍安全轨迹。
原文摘要 · Abstract (English)
Autonomous high-speed navigation through large, complex environments requires real-time generation of agile trajectories that are dynamically feasible, collision-free, and satisfy constraints. Most modern trajectory planning techniques rely on numerical optimization because high-quality, expressive trajectories that satisfy constraints can be systematically computed. However, strict requirements on computation time and the risk of numerical instability can limit the use of optimization-based planners in safety-critical situations. This work presents an optimization-free planning framework called STITCHER that leverages graph search to generate long-range trajectories by stitching short trajectory segments together in real time. STITCHER is shown to outperform modern optimization-based planners through its innovative planning architecture and several algorithmic developments that make real-time planning possible. Simulation results show safe trajectories through complex environments can be generated in milliseconds that cover tens of meters.
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