def get_fitness(self, individual):
""" Run the simulation and return the fitness """
state_machine = sm.StateMachine(self.start_positions,
self.random_events, self.sm_pars,
self.mode)
pytree = PyTree(individual[:],
behaviors=behaviors,
world_interface=state_machine,
verbose=self.verbose)
# run the Behavior Tree
ticks, _ = pytree.run_bt()
return fitness_function.compute_fitness(state_machine, pytree, ticks,
self.targets,
self.fitness_coeff)
def test_balance():
""" Test run of balancing with off gravity piece """
behavior_tree.load_settings_from_file(
'duplo_state_machine/BT_SETTINGS_BALANCE.yaml')
start_positions = []
start_positions.append(sm.Pos(-0.05, -0.1, 0.0))
start_positions.append(sm.Pos(0.0, -0.1, 0.0))
start_positions.append(sm.Pos(0.05, -0.1, 0.0))
state_machine = sm.StateMachine(start_positions, False)
goals = ['0 at pos (0.0, 0.0, 0.0192)?']
planner.plan(state_machine, behaviors, goals)
behavior_tree.load_settings_from_file(
'behavior_tree_learning/tests/BT_TEST_SETTINGS.yaml')
def test_croissant():
""" Test run of stacking four bricks in a structure looking somewhat like a croissant """
behavior_tree.load_settings_from_file(
'duplo_state_machine/BT_SETTINGS_CROISSANT.yaml')
start_positions = []
start_positions.append(sm.Pos(-0.05, -0.1, 0))
start_positions.append(sm.Pos(0, -0.1, 0))
start_positions.append(sm.Pos(0.05, -0.1, 0))
start_positions.append(sm.Pos(0.1, -0.1, 0))
state_machine = sm.StateMachine(start_positions, False)
goals = ['0 at pos (0.0, 0.0, 0.0)?', '1 at pos (0.0, 0.0, 0.0192)?', \
'2 at pos (0.016, -0.032, 0.0)?', '3 at pos (0.016, 0.032, 0.0)?']
planner.plan(state_machine, behaviors, goals)
behavior_tree.load_settings_from_file(
'behavior_tree_learning/tests/BT_TEST_SETTINGS.yaml')
def test_tower():
""" Test run of stacking three bricks in a tower """
behavior_tree.load_settings_from_file(
'duplo_state_machine/BT_SETTINGS_TOWER.yaml')
start_positions = []
start_positions.append(sm.Pos(-0.05, -0.1, 0))
start_positions.append(sm.Pos(0, -0.1, 0))
start_positions.append(sm.Pos(0.05, -0.1, 0))
state_machine = sm.StateMachine(start_positions, False)
goals = [
'0 at pos (0.0, 0.05, 0.0)?', '1 at pos (0.0, 0.05, 0.0192)?',
'2 at pos (0.0, 0.05, 0.0384)?'
]
planner.plan(state_machine, behaviors, goals)
behavior_tree.load_settings_from_file(
'behavior_tree_learning/tests/BT_TEST_SETTINGS.yaml')
def test_blocking():
""" Test run of shuffling bricks to avoid blocking """
behavior_tree.load_settings_from_file(
'duplo_state_machine/BT_SETTINGS_BLOCKING.yaml')
start_positions = []
start_positions.append(sm.Pos(0.0, -0.05, 0.0))
start_positions.append(sm.Pos(0.0, 0.05, 0.0))
start_positions.append(sm.Pos(-0.1, 0.0, 0.0))
state_machine = sm.StateMachine(start_positions, False)
goals = [
'0 at pos (-0.1, 0.0, 0.0)?', '1 at pos (-0.1, 0.0, 0.0192)?',
'2 at pos (0.0, 0.0, 0.0)?'
]
planner.plan(state_machine, behaviors, goals)
behavior_tree.load_settings_from_file(
'behavior_tree_learning/tests/BT_TEST_SETTINGS.yaml')