def __init__(self, car="kari", mqtt_broker="mqtt.eclipse.org"):
self.camera_sub = MQTTValueSub("donkey/%s/camera" % car, broker=mqtt_broker)
self.state_sub = MQTTValueSub("donkey/%s/state" % car, broker=mqtt_broker)
self.controller_pub = MQTTValuePub("donkey/%s/controls" % car, broker=mqtt_broker)
self.jpgToImg = JpgToImgArr()
self.img = np.zeros((40, 40))
self.state = None
self.speed = 0
def __init__(self, alg_type, sim, car_name=args.car_name):
self.args = define_config()
self.agent = Dreamer(self.args)
self.sim = sim
self.image = np.zeros((120, 160, 3))
self.observation = torch.zeros(
(1, 3, 64, 64)) # init observation, with batch dim
self.belief = torch.zeros(1,
self.args.belief_size,
device=self.args.device)
self.posterior_state = torch.zeros(1,
self.args.state_size,
device=self.args.device)
self.action = torch.zeros(1,
self.args.action_size,
device=self.args.device)
# self.act_history = torch.zeros(1, self.args.action_size*3, device=self.args.device)
self.speed = 0
self.step = 0
self.episode = 0
self.episode_reward = 0
self.replay_buffer = []
self.target_speed = 0
self.steering = 0
self.training = False
self.step_start = 0
self.buffers_sent = False
self.replay_buffer_pub = MQTTValuePub(car_name + "buffer",
broker="mqtt.eclipse.org")
self.replay_buffer_sub = MQTTValueSub(car_name + "buffer",
broker="mqtt.eclipse.org",
def_value=(0, True))
self.replay_buffer_received_pub = MQTTValuePub(
car_name + "buffer_received", broker="mqtt.eclipse.org")
self.replay_buffer_received_sub = MQTTValueSub(
car_name + "buffer_received",
broker="mqtt.eclipse.org",
def_value=0)
self.param_pub = MQTTValuePub(car_name + "param",
broker="mqtt.eclipse.org")
self.param_sub = MQTTValueSub(car_name + "param",
broker="mqtt.eclipse.org")
def __init__(self, donkey_name, mqtt_broker, sensor_size=(120, 160, 3)):
self.camera_sub = MQTTValueSub("donkey/%s/camera" % donkey_name,
broker=mqtt_broker)
self.controller_pub = MQTTValuePub("donkey/%s/controls" % donkey_name,
broker=mqtt_broker)
self.jpgToImg = JpgToImgArr()
self.sensor_size = sensor_size
def __init__(self,
car_name="Kari",
mqtt_broker="mqtt.eclipse.org",
realsense=False,
env_type="DonkeyCar"):
self.camera_sub = MQTTValueSub("donkey/%s/camera" % car_name,
broker=mqtt_broker)
if realsense:
self.state_sub = MQTTValueSub("donkey/%s/state" % car_name,
broker=mqtt_broker)
self.controller_pub = MQTTValuePub("donkey/%s/controls" % car_name,
broker=mqtt_broker)
self.jpgToImg = JpgToImgArr()
self.img = np.zeros((40, 40))
self.state = None
self.speed = 0
self.realsense = realsense
self.sim = env_type != "DonkeyCar"
import math
from docopt import docopt
import donkeycar as dk
import cv2
from donkeycar.parts.cv import CvImageView, ImgBGR2RGB, ImgRGB2BGR, ImageScale, ImgWriter, ArrowKeyboardControls
from donkeycar.parts.salient import SalientVis
from donkeycar.parts.network import MQTTValuePub, MQTTValueSub
from donkeycar.parts.transform import Lambda
from donkeycar.parts.image import JpgToImgArr
V = dk.vehicle.Vehicle()
args = docopt(__doc__)
print(args)
V.add(MQTTValueSub(name="donkey/%s/camera" % args["--name"], broker=args["--broker"]), outputs=["jpg"])
V.add(JpgToImgArr(), inputs=["jpg"], outputs=["img_arr"])
V.add(ImgBGR2RGB(), inputs=["img_arr"], outputs=["rgb"])
V.add(ImageScale(4.0), inputs=["rgb"], outputs=["lg_img"])
V.add(CvImageView(), inputs=["lg_img"])
V.add(ArrowKeyboardControls(), outputs=["control"])
V.add(MQTTValuePub(name="donkey/%s/controls" % args["--name"]), inputs=["control"])
record_path = args["--record"]
if record_path is not None:
class ImageSaver:
def __init__(self, path):
self.index = 0
self.path = path
threaded = True
inputs = ['angle', 'throttle']
V.add(cam, inputs=inputs, outputs=['camera/arr'], threaded=threaded)
#V.add(cam, outputs=["camera/arr"], threaded=True)
img_to_jpg = ImgArrToJpg()
V.add(img_to_jpg, inputs=["camera/arr"], outputs=["camera/jpg"])
pub_cam = MQTTValuePub("donkey/%s/camera" % cfg.DONKEY_UNIQUE_NAME,
broker=cfg.MQTT_BROKER)
V.add(pub_cam, inputs=["camera/jpg"])
sub_controls = MQTTValueSub("donkey/%s/controls" % cfg.DONKEY_UNIQUE_NAME,
def_value=(0., 0.),
broker=cfg.MQTT_BROKER)
V.add(sub_controls, outputs=["angle", "throttle"])
# steering_controller = PCA9685(cfg.STEERING_CHANNEL, cfg.PCA9685_I2C_ADDR, busnum=cfg.PCA9685_I2C_BUSNUM)
# steering = PWMSteering(controller=steering_controller,
# left_pulse=cfg.STEERING_LEFT_PWM,
# right_pulse=cfg.STEERING_RIGHT_PWM)
# throttle_controller = PCA9685(cfg.THROTTLE_CHANNEL, cfg.PCA9685_I2C_ADDR, busnum=cfg.PCA9685_I2C_BUSNUM)
# throttle = PWMThrottle(controller=throttle_controller,
# max_pulse=cfg.THROTTLE_FORWARD_PWM,
# zero_pulse=cfg.THROTTLE_STOPPED_PWM,
# min_pulse=cfg.THROTTLE_REVERSE_PWM)
# V.add(steering, inputs=['angle'])
def __init__(self, donkey_name, mqtt_broker):
self.camera_sub = MQTTValueSub("donkey/%s/camera" % donkey_name,
broker=mqtt_broker)
self.controller_pub = MQTTValuePub("donkey/%s/controls" % donkey_name,
broker=mqtt_broker)
self.jpgToImg = JpgToImgArr()
V = dk.Vehicle()
print("starting up", cfg.DONKEY_UNIQUE_NAME, "for remote management.")
cam = PiCamera(image_w=cfg.IMAGE_W,
image_h=cfg.IMAGE_H,
image_d=cfg.IMAGE_DEPTH)
V.add(cam, outputs=["camera/arr"], threaded=True)
img_to_jpg = ImgArrToJpg()
V.add(img_to_jpg, inputs=["camera/arr"], outputs=["camera/jpg"])
pub_cam = MQTTValuePub("donkey/%s/camera" % cfg.DONKEY_UNIQUE_NAME)
V.add(pub_cam, inputs=["camera/jpg"])
sub_controls = MQTTValueSub("donkey/%s/controls" % cfg.DONKEY_UNIQUE_NAME,
def_value=(0., 0.))
V.add(sub_controls, outputs=["angle", "throttle"])
steering_controller = ServoBlaster(cfg.STEERING_CHANNEL)
#PWM pulse values should be in the range of 100 to 200
assert (cfg.STEERING_LEFT_PWM <= 200)
assert (cfg.STEERING_RIGHT_PWM <= 200)
steering = PWMSteering(controller=steering_controller,
left_pulse=cfg.STEERING_LEFT_PWM,
right_pulse=cfg.STEERING_RIGHT_PWM)
from donkeycar.parts.actuator import Mini_HBridge_DC_Motor_PWM
motor = Mini_HBridge_DC_Motor_PWM(cfg.HBRIDGE_PIN_FWD, cfg.HBRIDGE_PIN_BWD)
V.add(steering, inputs=['angle'])
def __init__(self,
alg_type,
sim,
car_name=args.car_name,
encoder_update=args.encoder_update,
max_episode_steps=MAX_EPISODE_STEPS):
if encoder_update == "pixel":
print("Using Pixel encoder")
PARAMS["sac"]["encoder_critic_loss"] = True
PARAMS["sac"]["encoder_ae_loss"] = False
if encoder_update == "ae":
print("Using Autoencoder loss")
PARAMS["sac"]["encoder_critic_loss"] = False
PARAMS["sac"]["encoder_ae_loss"] = True
if encoder_update == "aesac":
print("Using autoencoder and critic loss")
PARAMS["sac"]["encoder_critic_loss"] = True
PARAMS["sac"]["encoder_ae_loss"] = True
self.agent = AE_SAC(PARAMS)
self.sim = sim
self.image = np.zeros((120, 160, 3))
self.command_history = np.zeros(3 * COMMAND_HISTORY_LENGTH)
self.state = np.vstack([
self.agent.process_im(self.image, IMAGE_SIZE, RGB)
for x in range(FRAME_STACK)
])
self.speed = 0
self.step = 0
self.episode = 0
self.episode_reward = 0
self.replay_buffer = []
self.max_episode_steps = max_episode_steps
self.target_speed = 0
self.steering = 0
self.training = False
self.step_start = 0
self.buffers_sent = False
self.replay_buffer_pub = MQTTValuePub(car_name + "buffer",
broker="mqtt.eclipse.org")
self.replay_buffer_sub = MQTTValueSub(car_name + "buffer",
broker="mqtt.eclipse.org",
def_value=(0, True))
self.replay_buffer_received_pub = MQTTValuePub(
car_name + "buffer_received", broker="mqtt.eclipse.org")
self.replay_buffer_received_sub = MQTTValueSub(
car_name + "buffer_received",
broker="mqtt.eclipse.org",
def_value=0)
self.param_pub = MQTTValuePub(car_name + "param",
broker="mqtt.eclipse.org")
self.param_sub = MQTTValueSub(car_name + "param",
broker="mqtt.eclipse.org")