Purpose / Use cases

This package is a thin boiler-plate package that connects computation (pure_pursuit) and communication (DDS/ROS 2).

This is necessary to make it easy to test the computation in isolation from communication. Likewise, this package separates out the integration/communication tests for this package.

Design

This is a thin wrapper around pure_pursuit.

The current pose is transformed using the corresponding tf topic, and then compute the control command.

Assumptions / Known limits

This node assumes the global tf graph has a transformation between trajectory and pose frames.

See apex_tf for more details on the limitations of the transforms API.

See the PurePursuit design doc for more details.

Inputs / Outputs / API

Inputs:

• tf topic: source frame is pose and target frame is trajectory (through apex_tf)
• trajectory topic (in the trajectory frame)
• vehicle pose topic (in the pose frame)
• pure_pursuit parameters

Outputs:

• vehicle motion controller topic
• diagnosis topic for the pure_pursuit

On top of this, the nodes can be configured either programmatically or via parameter file on construction.

Inner-workings / Algorithms

See pure_pursuit for more details.

Error detection and handling

Most error handling occurs inside rclcpp, inside the PurePursuit itself, or in the associated configuration class.

Security considerations

These components inherit security considerations from Node, BufferCore, and the core PurePursuit class.

Future extensions / Unimplemented parts

• tf internal library for the pose transformation
• The way to subscribe tf topic should be deterministic.

Related issues

• #2642: Initial implementation
• #2838: apex_app -> apex_auto