Planning

To make the car drive itself we first need to plan the way we want to go.

GPS

To do this, we're going to use gps to trace the route from our current location to our target location.

Carla GlobalRoutePlanner enables us to get the route from two points given a map. We have encapsulated this function within operators/carla_gps_op.py.

The following operator will compute the route from the current position to the objective_waypoints given an opendrive map.

  - id: carla_gps_op
    operator:
      python: ../../carla/carla_gps_op.py
      outputs:
        - gps_waypoints
      inputs:
        opendrive: oasis_agent/opendrive
        objective_waypoints: oasis_agent/objective_waypoints
        position: oasis_agent/position

The waypoints are defined as a an array of x, y, speed as float32 waypoints, with global coordinates.

Planner

The GPS waypoints does not take into account obstacles. To avoid collision, we can implement a motion planner that can avoid obstacles.

We're going to reuse a model called fot (Frenet Optimal Trajectory) as a black box, that take as input a starting location and a goal waypoints, as well as a list of obstacles and outputs the best waypoints to follow.

  - id: fot_op
    operator:
      python: operators/fot_op.py
      outputs:
        - waypoints
      inputs:
        position: oasis_agent/position
        obstacles: obstacle_location_op/obstacles
        gps_waypoints: carla_gps_op/gps_waypoints

To test both functionallities:

dora up
dora start graphs/oasis/oasis_agent_planning.yaml --attach

For more information on fot, go on our fot detail page