def Plan(self, dt, observed_world):
# NOTE: if training is enabled the action is set externally
if not self._set_action_externally:
observed_state = self.env._observer.Observe(observed_world)
action = self.Act(observed_state)
self._action = action
action = self._action
# set action to be executed
self._bark_behavior_model.ActionToBehavior(action)
trajectory = self._bark_behavior_model.Plan(dt, observed_world)
# NOTE: BARK requires models to have trajectories of the past
BehaviorModel.SetLastTrajectory(self, trajectory)
return trajectory
def Plan(self, dt, observed_world):
# NOTE: if training is enabled the action is set externally
if not self._set_action_externally:
observed_state = self._environment._observer.Observe(
observed_world)
self._action = self.Act(observed_state)
# NOTE: BARK expects (m, 1) actions
action = self._action
if isinstance(self.action_space, BoundedContinuous):
action = np.reshape(self._action, (-1, 1))
# set action to be executed
self._bark_behavior_model.ActionToBehavior(action)
trajectory = self._bark_behavior_model.Plan(dt, observed_world)
# NOTE: BARK requires models to have trajectories of the past
BehaviorModel.SetLastTrajectory(self, trajectory)
return trajectory