  The accelerated deployment of service robots have spawned a number of
algorithm variations to better handle real-world conditions. Many local
trajectory planning techniques have been deployed on practical robot systems
successfully. While most formulations of Dynamic Window Approach and Model
Predictive Control can progress along paths and optimize for additional
criteria, the use of pure path tracking algorithms is still commonplace.
Decades later, Pure Pursuit and its variants continues to be one of the most
commonly utilized classes of local trajectory planners. However, few Pure
Pursuit variants have been proposed with schema for variable linear velocities
- they either assume a constant velocity or fails to address the point at all.
This paper presents a variant of Pure Pursuit designed with additional
heuristics to regulate linear velocities, built atop the existing Adaptive
variant. The Regulated Pure Pursuit algorithm makes incremental improvements on
state of the art by adjusting linear velocities with particular focus on safety
in constrained and partially observable spaces commonly negotiated by deployed
robots.
  We present experiments with the Regulated Pure Pursuit algorithm on
industrial-grade service robots. We also provide a high-quality reference
implementation that is freely included ROS 2 Nav2 framework at
https://github.com/ros-planning/navigation2 for fast evaluation.

Robotics