DWPP: Dynamic Window Pure Pursuit Considering Velocity and Acceleration Constraints

TL;DR

DWPP addresses the mismatch between commanded and realized motion in pure pursuit by explicitly enforcing velocity and acceleration constraints. It does so by formulating command velocity computation in the velocity space and selecting the dynamic-window velocity closest to the path-curvature line $\\omega = \\kappa v$, yielding constraint-compliant commands and reduced overshoot. Real-robot experiments integrated with Nav2 show DWPP achieves superior tracking accuracy with zero constraint violations, at the cost of longer travel times, and the method is publicly available. The approach provides a practical, computationally efficient alternative for robust, high-curvature path tracking in mobile robots.

Abstract

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).

Figures (12)

• Figure 1: Processing flow of conventional pure pursuit methods and the proposed method.
• Figure 2: Geometric relationships between robot position, path, and lookahead position.
• Figure 3: Comparison of command velocity computations in the $v$--$\omega$ space. (a) DWPP selects an executable velocity within the dynamic window closest to the line $\omega=\kappa v$, whereas (b) conventional PP may select a velocity outside the dynamic window, which is subsequently clipped by constraints.
• Figure 4: Robot used in the experiment.
• Figure 5: Experimental environment.