Debug

Debug visualization

The visualization markers of the planning flow (Input, Model Predictive Trajectory, and Output) are explained here.

All the following markers can be visualized by

ros2 launch autoware_path_optimizer launch_visualiation.launch.xml vehilce_model:=sample_vehicle

The vehicle_model must be specified to make footprints with vehicle's size.

Input

• Path
  • The path generated in the behavior planner.
  • The semitransparent and thick, green and red band, that is visualized by default.

• Path Footprint
  • The path generated in the behavior planner is converted to footprints.
  • NOTE:
    • Check if there is no high curvature.
    • The path may be outside the drivable area in some cases, but it is okay to ignore it since the behavior planner does not support it.

• Drivable Area
  • The Drivable area generated in the behavior planner.
  • The skyblue left and right line strings, that is visualized by default.
  • NOTE:
    • Check if the path is almost inside the drivable area.
      • Then, the path_optimizer will try to make the trajectory fully inside the drivable area.
    • During avoidance or lane change by the behavior planner, please make sure that the drivable area is expanded correctly.

Model Predictive Trajectory (MPT)

• MPT Reference Trajectory
  • The reference trajectory points of model predictive trajectory.

• MPT Fixed Trajectory
  • The fixed trajectory points as a constraint of model predictive trajectory.

• Boundaries' Width
  • The boundaries' width is calculated from the drivable area line strings.

• Vehicle Circles
  • The vehicle's shape is represented by a set of circles.
  • The path_optimizer will try to make the these circles inside the above boundaries' width.

• Vehicle Circles on Trajectory
  • The vehicle's circles on the MPT trajectory.
  • Check if the circles are not so big compared to the road's width.

• MPT Trajectory
  • The optimized trajectory points by model predictive trajectory.
  • The footprints are supposed to be fully inside the drivable area.

Output

• Trajectory
  • The output trajectory.
  • The dark and thin, green and red band, that is visualized by default.

• Trajectory Footprint
  • The output trajectory is converted to footprints.

Calculation time

The path_optimizer consists of many functions such as boundaries' width calculation, collision-free planning, etc. We can see the calculation time for each function as follows.

Raw data

Enable option.enable_calculation_time_info or echo the topic as follows.

$ ros2 topic echo /planning/scenario_planning/lane_driving/motion_planning/path_optimizer/debug/calculation_time --field data
---
        insertFixedPoint:= 0.008 [ms]
        getPaddedTrajectoryPoints:= 0.002 [ms]
        updateConstraint:= 0.741 [ms]
        optimizeTrajectory:= 0.101 [ms]
        convertOptimizedPointsToTrajectory:= 0.014 [ms]
      getEBTrajectory:= 0.991 [ms]
          resampleReferencePoints:= 0.058 [ms]
          updateFixedPoint:= 0.237 [ms]
          updateBounds:= 0.22 [ms]
          updateVehicleBounds:= 0.509 [ms]
        calcReferencePoints:= 1.649 [ms]
        calcMatrix:= 0.209 [ms]
        calcValueMatrix:= 0.015 [ms]
          calcObjectiveMatrix:= 0.305 [ms]
          calcConstraintMatrix:= 0.641 [ms]
          initOsqp:= 6.896 [ms]
          solveOsqp:= 2.796 [ms]
        calcOptimizedSteerAngles:= 9.856 [ms]
        calcMPTPoints:= 0.04 [ms]
      getModelPredictiveTrajectory:= 12.782 [ms]
    optimizeTrajectory:= 12.981 [ms]
    applyInputVelocity:= 0.577 [ms]
    insertZeroVelocityOutsideDrivableArea:= 0.81 [ms]
      getDebugMarker:= 0.684 [ms]
      publishDebugMarker:= 4.354 [ms]
    publishDebugMarkerOfOptimization:= 5.047 [ms]
 generateOptimizedTrajectory:= 20.374 [ms]
  extendTrajectory:= 0.326 [ms]
  publishDebugData:= 0.008 [ms]
onPath:= 20.737 [ms]

Plot

With the following script, any calculation time of the above functions can be plot.

ros2 run autoware_path_optimizer calculation_time_plotter.py

You can specify functions to plot with the -f option.

ros2 run autoware_path_optimizer calculation_time_plotter.py -f "onPath, generateOptimizedTrajectory, calcReferencePoints"

Q&A for Debug

The output frequency is low

Check the function which is comparatively heavy according to this information.

For your information, the following functions for optimization and its initialization may be heavy in some complicated cases.

• MPT
  • initOsqp
  • solveOsqp

When a part of the trajectory has high curvature

Some of the following may have an issue. Please check if there is something weird by the visualization.

• Input Path
• Drivable Area
• Boundaries' Width

When the trajectory's shape is zigzag

Some of the following may have an issue. Please check if there is something weird by the visualization.

• Vehicle Circles on Trajectory