def main():
global default_model, default_scenario
beamng = BeamNGpy('localhost',
64256,
home='C:/Users/merie/Documents/BeamNG.research.v1.7.0.1')
#scenario = Scenario('smallgrid', 'spawn_objects_example')
scenario = Scenario(default_scenario,
'research_test',
description='Random driving for research')
vehicle = Vehicle('ego_vehicle', model=default_model, licence='PYTHON')
vehicle = setup_sensors(vehicle)
spawn = spawn_point(default_scenario)
scenario.add_vehicle(vehicle,
pos=spawn['pos'],
rot=spawn['rot'],
rot_quat=spawn['rot_quat'])
scenario.make(beamng)
bng = beamng.open()
bng.load_scenario(scenario)
bng.start_scenario()
vehicle.update_vehicle()
d1 = bng.poll_sensors(vehicle)
cum_list = []
bound = 0.0
for i in range(3):
for _ in range(45):
bound = bound + 0.0 # 0.1
# vehicle.save()
vehicle.update_vehicle()
d2 = bng.poll_sensors(vehicle)
throttle = 1.0
#throttle = random.uniform(0.0, 1.0)
steering = random.uniform(-1 * bound, bound)
brake = 0.0 #random.choice([0, 0, 0, 1])
vehicle.control(throttle=throttle, steering=steering, brake=brake)
pointName = "{}_{}".format(i, _)
cum_list.append(pointName)
vehicle.saveRecoveryPoint(pointName)
bng.step(20)
print("SEGMENT #{}: COMPARE DAMAGE".format(i))
damage_diff = compare_damage(d1, d2)
d1 = d2
# "Back up" 1 second -- load vehicle at that time in that position.
backup_pointName = backup(cum_list, 0.001)
print('recovering to {}'.format(pointName))
loadfile = vehicle.loadRecoveryPoint(backup_pointName)
print('loadfile is {}'.format(loadfile))
bng.pause()
vehicle.update_vehicle()
vehicle.load(loadfile)
#vehicle.load("vehicles/pickup/vehicle.save.json")
bng.resume()
#vehicle.startRecovering()
#time.sleep(1.5)
#vehicle.stopRecovering()
vehicle.update_vehicle()
bng.pause()
time.sleep(2)
# vehicle.load("vehicles/pickup/vehicle.save.json")
bng.resume()
bng.close()
def main():
random.seed(1703)
setup_logging()
beamng = BeamNGpy('localhost',
64256,
home='C:/Users/merie/Documents/BeamNG.research.v1.7.0.1')
state_cfg = Config()
parts_cfg = Config()
# Create a scenario in west_coast_usa
scenario = Scenario('west_coast_usa',
'research_test',
description='Random driving for research')
# Set up first vehicle, with two cameras, gforces sensor, lidar, electrical
# sensors, and damage sensors
vehicle = Vehicle('ego_vehicle',
model='etk800',
licence='RED',
color='Red')
vehicle = setup_sensors(vehicle)
scenario.add_vehicle(vehicle,
pos=(-717.121, 101, 118.675),
rot=None,
rot_quat=(0, 0, 0.3826834, 0.9238795))
# Compile the scenario and place it in BeamNG's map folder
#scenario.make(beamng)
# Start BeamNG and enter the main loop
bng = beamng.open(launch=True)
try:
#bng.hide_hud()
bng.set_deterministic() # Set simulator to be deterministic
bng.set_steps_per_second(60) # With 60hz temporal resolution
# Load and start the scenario
bng.load_scenario(scenario)
bng.start_scenario()
# Put simulator in pause awaiting further inputs
bng.pause()
pcfg = vehicle.get_part_config()
assert vehicle.skt
# Send random inputs to vehicle and advance the simulation 20 steps
#for _ in range(1024):
for _ in range(30):
throttle = random.uniform(0.0, 1.0)
steering = random.uniform(-1.0, 1.0)
brake = random.choice([0, 0, 0, 1])
vehicle.control(throttle=throttle, steering=steering, brake=brake)
# bng.step(20)
bng.step(20)
# Retrieve sensor data and show the camera data.
sensors = bng.poll_sensors(vehicle)
print('\n{} seconds passed.'.format(sensors['timer']['time']))
print("step in loop {}".format(_))
finally:
sensors = bng.poll_sensors(vehicle)
for s in sensors.keys():
print("{} : {}".format(s, sensors[s]))
damage_dict = sensors['damage']
state_cfg.update(sensors['damage'])
state_cfg.update(vehicle.state)
state_cfg.save('{}/state_cfg.json'.format(beamng.home))
vehicle.annotate_parts()
vehicle.update_vehicle()
#part_options = vehicle.get_part_options()
parts_cfg_dict = vehicle.get_part_config()
parts_cfg.load_values(vehicle.get_part_config())
#parts_cfg.update(vehicle.get_part_config())
parts_cfg.save('{}/parts_cfg.json'.format(beamng.home))
vehicle.save()
bng.close()
# reload scenario with saved config
random.seed(1703)
setup_logging()
beamng = BeamNGpy('localhost',
64256,
home='C:/Users/merie/Documents/BeamNG.research.v1.7.0.1')
loaded_config = state_cfg.load("{}/state_cfg.json".format(beamng.home))
scenario = Scenario('west_coast_usa',
'research_test',
description='Random driving for research')
vehicle = Vehicle('ego_vehicle',
model='etk800',
licence='RED',
color='Red')
vehicle = setup_sensors(vehicle)
vehicle.set_part_config(parts_cfg)
scenario.add_vehicle(vehicle,
pos=tuple(state_cfg.pos),
rot=None,
rot_quat=beamngpy.angle_to_quat(state_cfg.dir))
scenario.make(beamng)
bng = beamng.open(launch=True)
bng.spawn_vehicle(vehicle,
pos=tuple(state_cfg.pos),
rot=None,
rot_quat=beamngpy.angle_to_quat(state_cfg.dir))
# TODO: debug scenario restart
# scenario.restart()
try:
bng.hide_hud()
bng.set_deterministic() # Set simulator to be deterministic
bng.set_steps_per_second(60) # With 60hz temporal resolution
# Load and start the scenario
bng.load_scenario(scenario)
bng.start_scenario()
# Put simulator in pause awaiting further inputs
bng.pause()
assert vehicle.skt
vehicle.load()
# Send random inputs to vehicle and advance the simulation 20 steps
#for _ in range(1024):
for _ in range(30):
throttle = random.uniform(0.0, 1.0)
steering = random.uniform(-1.0, 1.0)
brake = random.choice([0, 0, 0, 1])
vehicle.control(throttle=throttle, steering=steering, brake=brake)
# bng.step(20)
bng.step(20)
# Retrieve sensor data and show the camera data.
sensors = bng.poll_sensors(vehicle)
print('\n{} seconds passed.'.format(sensors['timer']['time']))
print("step in loop {}".format(_))
finally:
sensors = bng.poll_sensors(vehicle)
for s in sensors.keys():
print("{} : {}".format(s, sensors[s]))
state_cfg.update(sensors['damage'])
state_cfg.update(vehicle.state)
state_cfg.save('{}/state_cfg.json'.format(beamng.home))
parts_cfg.update(vehicle.get_part_config())
parts_cfg.save('{}/parts_cfg.json'.format(beamng.home))
bng.close()
