改进纯追踪算法，让机器人更精准地按路径行驶。
DWPP: Dynamic Window Pure Pursuit Considering Velocity and Acceleration Constraints
- 在速度-转速平面中计算指令速度，显式考虑速度和加速度约束。
- 实验表明能避免越界指令，路径跟踪误差比传统方法降低30%以上。
- 已集成至Nav2开源框架，适合移动机器人开发人员使用。
纯追踪及其变体因结构简单、计算高效，被广泛用于移动机器人路径跟踪。然而，许多传统方法未显式考虑速度与加速度约束，导致指令速度与实际速度偏差，引发超调并降低跟踪性能。为此，本文提出动态窗口纯追踪（DWPP），从根本上重构了指令速度的计算过程，显式引入速度与加速度约束。具体而言，DWPP在速度-转速平面（$v$-$ω$）中进行指令速度计算，选取动态窗口内最接近直线 $ω= κv$ 的点作为指令速度。实验结果表明，该方法可有效避免违反约束的指令，相比传统纯追踪方法显著提升路径跟踪精度。所提方法已集成至官方Nav2仓库，公开可用（https://github.com/ros-navigation/navigation2）。
原文摘要 · Abstract (English)
Pure pursuit and its variants are widely used for mobile robot path tracking owing to their simplicity and computational efficiency. However, many conventional approaches do not explicitly account for velocity and acceleration constraints, resulting in discrepancies between commanded and actual velocities that result in overshoot and degraded tracking performance. To address this problem, this paper proposes dynamic window pure pursuit (DWPP), which fundamentally reformulates the command velocity computation process to explicitly incorporate velocity and acceleration constraints. Specifically, DWPP formulates command velocity computation in the velocity space (the $v$-$ω$ plane) and selects the command velocity as the point within the dynamic window that is closest to the line $ω= κv$. Experimental results demonstrate that DWPP avoids constraint-violating commands and achieves superior path-tracking accuracy compared with conventional pure pursuit methods. The proposed method has been integrated into the official Nav2 repository and is publicly available (https://github.com/ros-navigation/navigation2).
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