def slamming_test(ser):
for iteration in range(SLAMMING_ITERATIONS):
for actuator in range(5):
if iteration % 2 is 0:
send_angles[actuator] = MIN_ACTUATOR_ANGLE
else:
send_angles[actuator] = MAX_ACTUATOR_ANGLE
set_servo_angles(ser, send_angles)
time.sleep(SLAMMING_DELAY)
if __name__ == '__main__':
ser = init_serial()
print('Starting stress test')
#
# print('Starting sine test')
# sine_test()
# print('Finished sine test')
#
# time.sleep(1)
#
print('Starting vibration test')
vibration_test(ser)
print('Finished vibration test')
# time.sleep(1)
#
# print('Starting slamming test')
def __init__(self):
self.count = 0
self._seed()
self.viewer = None # to be used later for rendering
self.prev_state = None
# Load camera config
try:
f_cam_conf = open(CAMERA_CONFIG_FILENAME, 'r')
CAMERA_CONFIG.from_dict(json.load(f_cam_conf))
f_cam_conf.close()
print('Loaded camera config from \'' + CAMERA_CONFIG_FILENAME +
'\'')
except IOError:
print('Camera config not found, using default config\n')
# print(json.dumps(camera_config.to_dict(), sort_keys=True, indent=4))
# Load tracking parameters
self.ouc_params = capture.TrackParams()
self.actuator_params = capture.TrackParams()
try:
ouc_params_f = open(OUC_PARAMS_FILENAME, 'r')
self.ouc_params.from_dict(json.load(ouc_params_f))
ouc_params_f.close()
print('Loaded OUC params from \'' + OUC_PARAMS_FILENAME + '\'')
except IOError:
print('OUC params not found, stopping...\n')
exit(1)
try:
actuator_params_f = open(ACTUATOR_PARAMS_FILENAME, 'r')
self.actuator_params.from_dict(json.load(actuator_params_f))
actuator_params_f.close()
print('Loaded OUC params from \'' + ACTUATOR_PARAMS_FILENAME +
'\'')
except IOError:
print('OUC params not found, stopping...\n')
exit(1)
self.camera_capture = None
# Initialize hardware devices
self.arena_camera = capture.init_camera(CAMERA_CONFIG)
capture.camera_skip_frames(self.arena_camera, CAMERA_CONFIG)
self.serial = hardware_interface.init_serial()
zero_state = [0, 0, 0, 0, 0, 0, 0]
self.previous_pos = zero_state
# Observation Space
# [object posx, object posy, actuator1 pos.y, ... , actuator5 pos.y, actuator1 speed.y, ... , actuator5 speed.y]
high = np.array([np.inf] * 16)
self.observation_space = spaces.Box(low=-high, high=high)
# Continuous action space; one for each linear actuator (5 total)
# action space represents velocity
self.action_space = spaces.Box(-1, 1, (5, ))
self.prev_shaping = None # for reward calculation
self.time_previous = None
self.ouc_ui_pos = (0, 0)
self.actuators_ui_pos = [(0, 0), (0, 0), (0, 0), (0, 0), (0, 0)]
self._reset()