让机器人更安全地跟走复杂路径，避免因急转弯失控。
Reachability-Aware Time Scaling for Path Tracking
- 用可预测的加速度余量指导路径跟踪
- 在线路点路径上动态调整速度以保持可控性
- 适合对安全要求高的移动机器人系统
本文研究平面双积分系统在速度和加速度受限条件下，对离线规划生成的无碰撞航点路径进行跟踪。由于采样规划器需绕开障碍物，所得路径常含急弯和高曲率区域，即使几何上无碰撞，单步可达性也受加速度限制制约。为此，本文基于纯追踪风格的可达性引导二次规划（QP）跟踪器，引入单步加速度裕量。离线阶段，沿拟合的样条路径评估该裕量，并更新标量速度缩放策略，确保所需单步加速度始终低于可用上限。在线阶段，采用相同的前瞻跟踪结构实现缩放后的参考路径跟踪。
原文摘要 · Abstract (English)
This paper studies tracking of collision-free waypoint paths produced by an offline planner for a planar double-integrator system with bounded speed and acceleration. Because sampling-based planners must route around obstacles, the resulting waypoint paths can contain sharp turns and high-curvature regions, so one-step reachability under acceleration limits becomes critical even when the path geometry is collision-free. We build on a pure-pursuit-style, reachability-guided quadratic-program (QP) tracker with a one-step acceleration margin. Offline, we evaluate this margin along a spline fitted to the waypoint path and update a scalar speed-scaling profile so that the required one-step acceleration remains below the available bound. Online, the same look-ahead tracking structure is used to track the scaled reference.
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