def read_sensor_cache_of(self, vehicle: Vehicle, _: Scenario) -> Polygon:
from shapely.geometry import Polygon
bbox_points = vehicle.get_bbox()
shell = tuple(map(lambda pos: bbox_points[pos][0:2],
["near_bottom_left", "far_bottom_left", "far_bottom_right", "near_bottom_right"]))
return Polygon(shell=shell)
def main():
setup_logging()
beamng = BeamNGpy('localhost',
64256,
home='C:/Users/merie/Documents/BeamNG.research.v1.7.0.1')
scenario = Scenario(
'west_coast_usa',
'lidar_tour',
description='Tour through the west coast gathering Lidar data')
vehicle = Vehicle('ego_vehicle', model='etk800', licence='LIDAR')
vehicle = setup_sensors(vehicle)
lidar = setup_lidar('hood')
vehicle.attach_sensor('lidar', lidar)
spawn_pt = spawn_point()
ego_pos = spawn_pt['pos']
ego_rot_quat = spawn_pt['rot_quat']
scenario.add_vehicle(vehicle, pos=ego_pos, rot=None, rot_quat=ego_rot_quat)
tvs = traffic_vehicles()
scenario.make(beamng)
bng = beamng.open(launch=True)
#try:
bng.load_scenario(scenario)
bng.set_steps_per_second(60)
bng.set_deterministic()
bng.hide_hud()
bng.start_scenario()
vehicle.ai_set_mode('traffic')
vehicle.ai_set_aggression(0.5)
vehicle.ai_drive_in_lane(True)
#vehicle.ai_set_speed(16, mode='limit')
#vehicle.ai_set_target('traffic')
bng.switch_vehicle(vehicle)
damage_prev = None
start = time.time()
end = time.time()
bng.pause()
print("Bounding box: {}".format(vehicle.get_bbox()))
with open('lidar_data.csv', 'w') as f:
f.write(
"TIMESTAMP,VEHICLE_POSITION,VEHICLE_ORIENTATION,VELOCITY,LIDAR,CRASH\n"
)
for _ in range(1024):
sensors = bng.poll_sensors(vehicle)
points = sensors['lidar']['points']
damage = sensors['damage']
v_state = vehicle.state
print("vehicle_state = {}".format(v_state))
print("vehicle_state[pos] = {}".format(v_state['pos']))
print("vehicle_state[dir] = {}".format(v_state['dir']))
print("Vehicle bounding box:{}".format(vehicle.get_bbox()))
#ai_state = vehicle.ai_get_state()
#print("ai_state = {}".format(ai_state))
new_damage = diff_damage(damage, damage_prev)
damage_prev = damage
#print("new damage = {}".format(new_damage))
print()
f.write("{},{},{},{},{},{}\n".format(_ * 0.5, v_state['pos'],
v_state['dir'],
v_state['vel'],
points.tolist(),
str(new_damage)))
#bng.step(30, wait=False)
bng.step(30)
#print("Time passed since last step: {}".format(time.time() - end))
end = time.time()
#print("Time passed since scenario begun: {}\n".format(end - start))
#screenrecord()
if end - start >= 30:
#bng.close()
continue
return center
def rotate(vec, h, v):
rot_x = np.cos(h) * vec[0] - np.sin(h) * vec[1]
rot_y = np.sin(h) * vec[0] + np.cos(h) * vec[1]
rot_z = np.sin(v) * rot_y + np.cos(v) * vec[2]
return np.array([rot_x, rot_y, rot_z])
with beamng as bng:
bng.load_scenario(scenario)
bng.start_scenario()
bng.pause()
center = get_bbox_center(vehicle.get_bbox())
center[1] -= 0.75 # move center back a bit to get more of the vehicle
cam_off = center + np.array(
[3.5, 0, 0]) # Offset the camera 4 meters in front of the center
images = []
for h in variations:
image_row = []
for v in variations:
current_pos = rotate(cam_off, h, v)
current_dir = center - current_pos
camera.pos = current_pos
camera.direction = current_dir
image = bng.poll_sensors(vehicle)['camera']['colour']
