def __init__(self, node_name):
super().__init__(node_name, node_type=NodeType.PERCEPTION)
# parameters
self.publish_freq = DTParam("~publish_freq", -1)
# utility objects
self.bridge = CvBridge()
self.reminder = DTReminder(frequency=self.publish_freq.value)
# subscribers
self.sub_img = rospy.Subscriber("~image_in",
CompressedImage,
self.cb_image,
queue_size=1,
buff_size="10MB")
# publishers
self.pub_img = rospy.Publisher(
"~image_out",
Image,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help="Raw image",
)
def __init__(self):
super().__init__()
events_dir = STATS_CATEGORY_TO_DIR["event"]
usage_dir = STATS_CATEGORY_TO_DIR["usage"]
# ---
self._shutdown = False
self._providers: List[StatisticsProvider] = []
self._outbox = StatisticsUploader()
self._timer = DTReminder(frequency=FREQUENCY.EVERY_MINUTE)
# register providers
# - stats/events/ dir
self._providers.extend(glob_event_providers(events_dir, "*.json"))
# - stats/usage/ dirs
self._providers.extend(
glob_usage_providers(os.path.join(usage_dir, "disk_image"),
"*.json", "disk_image"))
self._providers.extend(
glob_usage_providers(os.path.join(usage_dir, "init_sd_card"),
"*.json", "init_sd_card"))
# - docker/ps
self._providers.append(DockerPSProvider(FREQUENCY.EVERY_MINUTE))
# - docker/images
self._providers.append(DockerImagesProvider(FREQUENCY.EVERY_MINUTE))
# - uptime
self._providers.append(UptimeProvider(FREQUENCY.EVERY_30_MINUTES))
# - network/configuration
self._providers.append(
NetworkConfigurationProvider(FREQUENCY.EVERY_1_HOUR))
# - ros/graph
self._providers.append(ROSGraphProvider(FREQUENCY.EVERY_30_MINUTES))
# - health
self._providers.append(HealthProvider(FREQUENCY.EVERY_30_MINUTES))
# - network/public_ip
self._providers.append(PublicIPProvider(FREQUENCY.ONESHOT))
# - geolocation
self._providers.append(GeolocationProvider(FREQUENCY.ONESHOT))
# - battery/history
self._providers.append(BatteryHistoryProvider(FREQUENCY.EVERY_2_HOURS))
# - battery/info
self._providers.append(BatteryInfoProvider(FREQUENCY.ONESHOT))
# - lsusb
self._providers.append(LSUSBProvider(FREQUENCY.EVERY_2_HOURS))
# - wireless/status
self._providers.append(
WirelessStatusProvider(FREQUENCY.EVERY_30_MINUTES))
# - robot/hostname
self._providers.append(RobotHostnameProvider())
# - robot/type
self._providers.append(RobotTypeProvider())
# - robot/configuration
self._providers.append(RobotConfigurationProvider())
# launch outbox
self._outbox.start()
def __init__(self):
super(AprilTagDetector,
self).__init__(node_name='apriltag_detector_node',
node_type=NodeType.PERCEPTION)
# get static parameters
self.family = rospy.get_param('~family', 'tag36h11')
self.nthreads = rospy.get_param('~nthreads', 1)
self.quad_decimate = rospy.get_param('~quad_decimate', 1.0)
self.quad_sigma = rospy.get_param('~quad_sigma', 0.0)
self.refine_edges = rospy.get_param('~refine_edges', 1)
self.decode_sharpening = rospy.get_param('~decode_sharpening', 0.25)
self.tag_size = rospy.get_param('~tag_size', 0.065)
# dynamic parameter
self.detection_freq = DTParam('~detection_freq',
default=-1,
param_type=ParamType.INT,
min_value=-1,
max_value=30)
self._detection_reminder = DTReminder(
frequency=self.detection_freq.value)
# camera info
self._camera_parameters = None
self._camera_frame = None
# create detector object
self._at_detector = Detector(families=self.family,
nthreads=self.nthreads,
quad_decimate=self.quad_decimate,
quad_sigma=self.quad_sigma,
refine_edges=self.refine_edges,
decode_sharpening=self.decode_sharpening)
# create a CV bridge object
self._bridge = CvBridge()
# create subscribers
self._img_sub = rospy.Subscriber('image_rect', Image, self._img_cb)
self._cinfo_sub = rospy.Subscriber('camera_info', CameraInfo,
self._cinfo_cb)
# create publishers
self._img_pub = rospy.Publisher('tag_detections_image/compressed',
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.VISUALIZATION)
self._tag_pub = rospy.Publisher('tag_detections',
AprilTagDetectionArray,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION)
self._img_pub_busy = False
# create TF broadcaster
self._tf_bcaster = tf.TransformBroadcaster()
# spin forever
rospy.spin()
def __init__(self, category: str, key: str, frequency: float):
self._category = category
self._key = key
self._frequency = frequency or 0
self._ever_run = False
self._reminder = None if self.one_shot else DTReminder(
frequency=self._frequency)
def __init__(self, node_name):
super().__init__(node_name, node_type=NodeType.PERCEPTION)
# parameters
self.publish_freq = DTParam("~publish_freq", -1)
self.alpha = DTParam("~alpha", 0.0)
# utility objects
self.jpeg = TurboJPEG()
self.reminder = DTReminder(frequency=self.publish_freq.value)
self.camera_model = None
self.rect_camera_info = None
self.mapx, self.mapy = None, None
# subscribers
self.sub_img = rospy.Subscriber(
"~image_in",
CompressedImage,
self.cb_image,
queue_size=1,
buff_size='10MB'
)
self.sub_camera_info = rospy.Subscriber(
"~camera_info_in",
CameraInfo,
self.cb_camera_info,
queue_size=1
)
# publishers
self.pub_img = rospy.Publisher(
"~image/compressed",
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help="Rectified image (i.e., image with no distortion effects from the lens)."
)
self.pub_camera_info = rospy.Publisher(
"~camera_info",
CameraInfo,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help="Camera parameters for the (virtual) rectified camera."
)
def __init__(self, callback, logger: Logger = None):
self._devices = []
self._info = None
self._data = None
self._device = None
self._interaction: Optional[BatteryInteraction] = BatteryInteraction(
name="get_info",
command=b'??',
check=lambda d: 'FirmwareVersion' in d,
callback=lambda d: setattr(self, '_info', self._format_info(d)))
self._is_shutdown = False
self._logger = logger
if not callable(callback):
raise ValueError('Callback must be a callable object.')
self._callback = callback
self._reset_reminder = DTReminder(period=5)
self._worker = Thread(target=self._work)
self._history = BatteryHistory()
def __init__(self):
super(DistributedTFNode,
self).__init__(node_name='distributed_tf_node',
node_type=NodeType.SWARM)
# get static parameters
self.robot_hostname = rospy.get_param('~veh')
self.map_name = _sanitize_hostname(rospy.get_param('~map'))
self.tag_id = rospy.get_param('~tag_id')
self.min_distance_odom = rospy.get_param('~min_distance_odom')
self.max_time_between_poses = rospy.get_param(
'~max_time_between_poses')
# define local reference frames' names
self._tag_mount = f'{self.robot_hostname}/tag_mount'
self._footprint_frame = f'{self.robot_hostname}/footprint'
# create communication group
self._group = DTCommunicationGroup("/autolab/tf", AutolabTransform)
# create static tfs holder and access semaphore
self._static_tfs = {}
self._static_tfs_sem = threading.Semaphore(1)
self._tf_buffer = tf2_ros.Buffer()
self._tf_listener = tf2_ros.TransformListener(self._tf_buffer)
# create publishers
self._tf_pub = self._group.Publisher()
# fetch/publish right away and then set timers
if self.tag_id != '__NOTSET__':
threading.Thread(target=self._fetch_tag_tf).start()
self._pub_timer = rospy.Timer(
rospy.Duration(self.PUBLISH_TF_STATIC_EVERY_SECS),
self._publish_static_tfs)
# setup subscribers for odometry
self._odo_sub = rospy.Subscriber("~odometry_in",
Odometry,
self._cb_odometry,
queue_size=1)
self._pose_last = None
self._reminder = DTReminder(frequency=10)
class DecoderNode(DTROS):
def __init__(self, node_name):
super().__init__(node_name, node_type=NodeType.PERCEPTION)
# parameters
self.publish_freq = DTParam("~publish_freq", -1)
# utility objects
self.bridge = CvBridge()
self.reminder = DTReminder(frequency=self.publish_freq.value)
# subscribers
self.sub_img = rospy.Subscriber("~image_in",
CompressedImage,
self.cb_image,
queue_size=1,
buff_size="10MB")
# publishers
self.pub_img = rospy.Publisher(
"~image_out",
Image,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help="Raw image",
)
def cb_image(self, msg):
# make sure this matters to somebody
if not self.pub_img.anybody_listening():
return
# make sure the node is not switched off
if not self.switch:
return
# make sure this is a good time to publish (always keep this as last check)
if not self.reminder.is_time(frequency=self.publish_freq.value):
return
# turn 'compressed image message' into 'raw image'
with self.profiler("/cb/image/decode"):
img = self.bridge.compressed_imgmsg_to_cv2(msg)
# turn 'raw image' into 'raw image message'
with self.profiler("/cb/image/serialize"):
out_msg = self.bridge.cv2_to_imgmsg(img, "bgr8")
# maintain original header
out_msg.header = msg.header
# publish image
self.pub_img.publish(out_msg)
class Battery:
def __init__(self, callback, logger: Logger = None):
self._devices = []
self._info = None
self._data = None
self._device = None
self._interaction: Optional[BatteryInteraction] = BatteryInteraction(
name="get_info",
command=b'??',
check=lambda d: 'FirmwareVersion' in d,
callback=lambda d: setattr(self, '_info', self._format_info(d)))
self._is_shutdown = False
self._logger = logger
if not callable(callback):
raise ValueError('Callback must be a callable object.')
self._callback = callback
self._reset_reminder = DTReminder(period=5)
self._worker = Thread(target=self._work)
self._history = BatteryHistory()
def start(self, block: bool = False, quiet: bool = True):
if block:
return self._work(quiet=quiet)
else:
self._worker.start()
def join(self):
if self._worker.is_alive():
self._worker.join()
def is_shutdown(self):
return self._is_shutdown
def shutdown(self):
# This is NOT a battery shutdown, it simply shuts down the drivers
self._is_shutdown = True
self.join()
def turn_off(self,
timeout: int = 20,
wait: bool = False,
callback: Optional[Callable] = None):
# This is a battery shutdown, the power will be cut off after `timeout` seconds
firmware_version = self.info.get("version")
# noinspection PyBroadException
try:
# multi-firmware support
if semver.compare(firmware_version, "2.0.0") == 0:
timeout_str = f'{timeout}'.zfill(2)
self._interaction = BatteryInteraction(
name="turn_off",
command=f'Q{timeout_str}'.encode('utf-8'),
check=lambda d: d.get('TTL(sec)', None) == timeout,
callback=callback,
)
elif semver.compare(firmware_version, "2.0.1") >= 0:
self._interaction = BatteryInteraction(
name="turn_off",
command="QQ".encode('utf-8'),
check=lambda d: d.get('QACK', None) is not None,
callback=callback)
else:
raise Exception()
except Exception:
self._logger.warning(
f"Unknown/Unsupported battery firmware: {firmware_version}")
if wait:
self._interaction.join()
@property
def info(self):
return self._info
@property
def data(self):
return self._data
@data.setter
def data(self, data):
self._data = data
self._chew_on_data()
def history(self):
return self._history.get()
def _find_device(self):
vid_pid_match = "VID:PID={}:{}".format(BATTERY_PCB16_READY_VID,
BATTERY_PCB16_READY_PID)
ports = serial_grep(vid_pid_match)
self._devices = [p.device for p in ports] # ['/dev/ttyACM0', ...]
def _chew_on_data(self):
if self._data and self._info:
out = {
"present": True,
"charging": self._data['input_voltage'] >= (5.0 / 2),
**self._data
}
self._callback(out)
self._history.add(self._data)
def _read_next(self, dev, quiet: bool = True):
try:
raw = dev.read_until().decode('utf-8', 'ignore')
cleaned = re.sub(r"\x00\s*", "", raw).rstrip()
cleaned = re.sub(r"-\s+", "-", cleaned)
try:
# if "}{" present, get the first for checking shutdown ACK
if "}{" in cleaned:
cleaned = cleaned.split("}{")[0] + "}"
parsed = yaml.load(cleaned, yaml.SafeLoader)
return parsed
except yaml.YAMLError as e:
if self._logger:
self._logger.error(str(e))
return None
except BaseException as e:
if quiet:
# do not print, it would swamp the logs
pass
else:
raise e
def _work(self, quiet: bool = True):
while True:
if self._is_shutdown:
return
# ---
# if we don't have a battery device, search again
if len(self._devices) == 0:
self._find_device()
# if we still don't have it, just sleep for 5 seconds
if len(self._devices) == 0:
self._logger.warning(
'No battery found. Retrying in 5 seconds.')
else:
# we have at least one candidate device, try reading
for device in self._devices:
with serial.Serial(device, BATTERY_PCB16_BAUD_RATE) as dev:
# once the device is open, try reading from it forever
# break only on unknown errors
while True:
if self._is_shutdown:
return
# ---
if self._data is not None:
# we were able to read from the battery at least once,
# consume any pending interaction
if self._interaction.active:
iname, icmd = self._interaction.name, self._interaction.command
# there is a command to be sent, send it and continue
self._logger.debug(
f"Pending interaction '{iname}' found. "
f"Sending {str(icmd)} to the battery")
dev.write(self._interaction.command)
dev.flush()
# ---
try:
parsed = self._read_next(dev, quiet=quiet)
if parsed is None:
continue
# first time we read?
if self._device is None:
self._device = device
self._logger.info(
'Battery found at {}.'.format(device))
# distinguish between 'data' packet and others
if 'SOC(%)' in parsed:
# this is a 'data' packet
self.data = self._format_data(parsed)
elif self._interaction.active:
iname = self._interaction.name
self._logger.debug(
f"Received (candidate) response to "
f"interaction '{iname}': {str(parsed)}"
)
if self._interaction.check(parsed):
self._logger.debug(
f"Received valid response to "
f"interaction '{iname}': {str(parsed)}"
)
# complete interaction
self._interaction.complete(parsed)
except BaseException as e:
if quiet:
traceback.print_exc()
break
raise e
if self._logger:
self._logger.warning(
'An error occurred while reading from the battery.')
# allow 5 seconds for things to reset
self._reset_reminder.reset()
while not self._reset_reminder.is_time():
if self._is_shutdown:
return
time.sleep(0.5)
@staticmethod
def _format_data(data):
return {
"temperature": round(KELVIN_TO_CELSIUS(data['CellTemp(degK)']), 2),
"cell_voltage": round(float(data['CellVoltage(mV)']) / 1000, 2),
"input_voltage":
round(float(data['ChargerVoltage(mV)']) / 1000, 2),
"current": round(float(data['Current(mA)']) / 1000, 2),
"cycle_count": data['CycleCount'],
"percentage": data['SOC(%)'],
"time_to_empty": int(data['TimeToEmpty(min)'] * 60),
"usb_out_1_voltage": round(float(data['USB OUT-1(mV)']) / 1000, 2),
"usb_out_2_voltage": round(float(data['USB OUT-2(mV)']) / 1000, 2)
}
@staticmethod
def _format_info(info):
boot_data = str(info["BootData"])
firmware_version = str(info["FirmwareVersion"])
major, minor, patch, *_ = firmware_version + "000"
yy, mm, dd = boot_data[3:5], boot_data[5:7], boot_data[7:9]
return {
"version": f"{major}.{minor}.{patch}",
"boot": {
"version": boot_data[0],
"pcb_version": boot_data[1:3],
"date": f"{mm}/{dd}/{yy}"
},
"serial_number": info["SerialNumber"]
}
def __init__(self):
super(AprilTagDetector, self).__init__(
node_name='apriltag_detector_node',
node_type=NodeType.PERCEPTION
)
# get static parameters
self.family = rospy.get_param('~family', 'tag36h11')
self.ndetectors = rospy.get_param('~ndetectors', 1)
self.nthreads = rospy.get_param('~nthreads', 1)
self.quad_decimate = rospy.get_param('~quad_decimate', 1.0)
self.quad_sigma = rospy.get_param('~quad_sigma', 0.0)
self.refine_edges = rospy.get_param('~refine_edges', 1)
self.decode_sharpening = rospy.get_param('~decode_sharpening', 0.25)
self.tag_size = rospy.get_param('~tag_size', 0.065)
self.rectify_alpha = rospy.get_param('~rectify_alpha', 0.0)
# dynamic parameter
self.detection_freq = DTParam(
'~detection_freq',
default=-1,
param_type=ParamType.INT,
min_value=-1,
max_value=30
)
self._detection_reminder = DTReminder(frequency=self.detection_freq.value)
# camera info
self._camera_parameters = None
self._mapx, self._mapy = None, None
# create detector object
self._detectors = [Detector(
families=self.family,
nthreads=self.nthreads,
quad_decimate=self.quad_decimate,
quad_sigma=self.quad_sigma,
refine_edges=self.refine_edges,
decode_sharpening=self.decode_sharpening
) for _ in range(self.ndetectors)]
self._renderer_busy = False
# create a CV bridge object
self._jpeg = TurboJPEG()
# create subscribers
self._img_sub = rospy.Subscriber(
'~image',
CompressedImage,
self._img_cb,
queue_size=1,
buff_size='20MB'
)
self._cinfo_sub = rospy.Subscriber(
'~camera_info',
CameraInfo,
self._cinfo_cb,
queue_size=1
)
# create publisher
self._tag_pub = rospy.Publisher(
'~detections',
AprilTagDetectionArray,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_help='Tag detections',
)
self._img_pub = rospy.Publisher(
'~detections/image/compressed',
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.VISUALIZATION,
dt_help='Camera image with tag publishs superimposed',
)
# create thread pool
self._workers = ThreadPoolExecutor(self.ndetectors)
self._tasks = [None] * self.ndetectors
# create TF broadcaster
self._tf_bcaster = tf.TransformBroadcaster()
class AprilTagDetector(DTROS):
def __init__(self):
super(AprilTagDetector, self).__init__(
node_name='apriltag_detector_node',
node_type=NodeType.PERCEPTION
)
# get static parameters
self.family = rospy.get_param('~family', 'tag36h11')
self.ndetectors = rospy.get_param('~ndetectors', 1)
self.nthreads = rospy.get_param('~nthreads', 1)
self.quad_decimate = rospy.get_param('~quad_decimate', 1.0)
self.quad_sigma = rospy.get_param('~quad_sigma', 0.0)
self.refine_edges = rospy.get_param('~refine_edges', 1)
self.decode_sharpening = rospy.get_param('~decode_sharpening', 0.25)
self.tag_size = rospy.get_param('~tag_size', 0.065)
self.rectify_alpha = rospy.get_param('~rectify_alpha', 0.0)
# dynamic parameter
self.detection_freq = DTParam(
'~detection_freq',
default=-1,
param_type=ParamType.INT,
min_value=-1,
max_value=30
)
self._detection_reminder = DTReminder(frequency=self.detection_freq.value)
# camera info
self._camera_parameters = None
self._mapx, self._mapy = None, None
# create detector object
self._detectors = [Detector(
families=self.family,
nthreads=self.nthreads,
quad_decimate=self.quad_decimate,
quad_sigma=self.quad_sigma,
refine_edges=self.refine_edges,
decode_sharpening=self.decode_sharpening
) for _ in range(self.ndetectors)]
self._renderer_busy = False
# create a CV bridge object
self._jpeg = TurboJPEG()
# create subscribers
self._img_sub = rospy.Subscriber(
'~image',
CompressedImage,
self._img_cb,
queue_size=1,
buff_size='20MB'
)
self._cinfo_sub = rospy.Subscriber(
'~camera_info',
CameraInfo,
self._cinfo_cb,
queue_size=1
)
# create publisher
self._tag_pub = rospy.Publisher(
'~detections',
AprilTagDetectionArray,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_help='Tag detections',
)
self._img_pub = rospy.Publisher(
'~detections/image/compressed',
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.VISUALIZATION,
dt_help='Camera image with tag publishs superimposed',
)
# create thread pool
self._workers = ThreadPoolExecutor(self.ndetectors)
self._tasks = [None] * self.ndetectors
# create TF broadcaster
self._tf_bcaster = tf.TransformBroadcaster()
def on_shutdown(self):
self.loginfo('Shutting down workers pool')
self._workers.shutdown()
def _cinfo_cb(self, msg):
# create mapx and mapy
H, W = msg.height, msg.width
# create new camera info
self.camera_model = PinholeCameraModel()
self.camera_model.fromCameraInfo(msg)
# find optimal rectified pinhole camera
with self.profiler('/cb/camera_info/get_optimal_new_camera_matrix'):
rect_K, _ = cv2.getOptimalNewCameraMatrix(
self.camera_model.K,
self.camera_model.D,
(W, H),
self.rectify_alpha
)
# store new camera parameters
self._camera_parameters = (rect_K[0, 0], rect_K[1, 1], rect_K[0, 2], rect_K[1, 2])
# create rectification map
with self.profiler('/cb/camera_info/init_undistort_rectify_map'):
self._mapx, self._mapy = cv2.initUndistortRectifyMap(
self.camera_model.K,
self.camera_model.D,
None,
rect_K,
(W, H),
cv2.CV_32FC1
)
# once we got the camera info, we can stop the subscriber
self.loginfo('Camera info message received. Unsubscribing from camera_info topic.')
# noinspection PyBroadException
try:
self._cinfo_sub.shutdown()
except BaseException:
pass
def _detect(self, detector_id, msg):
# turn image message into grayscale image
with self.profiler('/cb/image/decode'):
img = self._jpeg.decode(msg.data, pixel_format=TJPF_GRAY)
# run input image through the rectification map
with self.profiler('/cb/image/rectify'):
img = cv2.remap(img, self._mapx, self._mapy, cv2.INTER_NEAREST)
# detect tags
with self.profiler('/cb/image/detection'):
tags = self._detectors[detector_id].detect(
img, True, self._camera_parameters, self.tag_size)
# pack detections into a message
tags_msg = AprilTagDetectionArray()
tags_msg.header.stamp = msg.header.stamp
tags_msg.header.frame_id = msg.header.frame_id
for tag in tags:
# turn rotation matrix into quaternion
q = _matrix_to_quaternion(tag.pose_R)
p = tag.pose_t.T[0]
# create single tag detection object
detection = AprilTagDetection(
transform=Transform(
translation=Vector3(
x=p[0],
y=p[1],
z=p[2]
),
rotation=Quaternion(
x=q[0],
y=q[1],
z=q[2],
w=q[3]
)
),
tag_id=tag.tag_id,
tag_family=str(tag.tag_family),
hamming=tag.hamming,
decision_margin=tag.decision_margin,
homography=tag.homography.flatten().astype(np.float32).tolist(),
center=tag.center.tolist(),
corners=tag.corners.flatten().tolist(),
pose_error=tag.pose_err
)
# add detection to array
tags_msg.detections.append(detection)
# publish tf
self._tf_bcaster.sendTransform(
p.tolist(),
q.tolist(),
msg.header.stamp,
'tag/{:s}'.format(str(tag.tag_id)),
msg.header.frame_id
)
# publish detections
self._tag_pub.publish(tags_msg)
# update healthy frequency metadata
self._tag_pub.set_healthy_freq(self._img_sub.get_frequency())
self._img_pub.set_healthy_freq(self._img_sub.get_frequency())
# render visualization (if needed)
if self._img_pub.anybody_listening() and not self._renderer_busy:
self._renderer_busy = True
Thread(target=self._render_detections, args=(msg, img, tags)).start()
def _img_cb(self, msg):
# make sure we have received camera info
if self._camera_parameters is None:
return
# make sure we have a rectification map available
if self._mapx is None or self._mapy is None:
return
# make sure somebody wants this
if (not self._img_pub.anybody_listening()) and (not self._tag_pub.anybody_listening()):
return
# make sure this is a good time to detect (always keep this as last check)
if not self._detection_reminder.is_time(frequency=self.detection_freq.value):
return
# make sure we are still running
if self.is_shutdown:
return
# ---
# find the first available worker (if any)
for i in range(self.ndetectors):
if self._tasks[i] is None or self._tasks[i].done():
# submit this image to the pool
self._tasks[i] = self._workers.submit(self._detect, i, msg)
break
def _render_detections(self, msg, img, detections):
with self.profiler('/publishs_image'):
# get a color buffer from the BW image
img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
# draw each tag
for detection in detections:
for idx in range(len(detection.corners)):
cv2.line(
img,
tuple(detection.corners[idx - 1, :].astype(int)),
tuple(detection.corners[idx, :].astype(int)),
(0, 255, 0)
)
# draw the tag ID
cv2.putText(
img,
str(detection.tag_id),
org=(
detection.corners[0, 0].astype(int) + 10,
detection.corners[0, 1].astype(int) + 10
),
fontFace=cv2.FONT_HERSHEY_SIMPLEX,
fontScale=0.8,
color=(0, 0, 255)
)
# pack image into a message
img_msg = CompressedImage()
img_msg.header.stamp = msg.header.stamp
img_msg.header.frame_id = msg.header.frame_id
img_msg.format = 'jpeg'
img_msg.data = self._jpeg.encode(img)
# ---
self._img_pub.publish(img_msg)
self._renderer_busy = False
class StatisticsWorker(Thread):
def __init__(self):
super().__init__()
events_dir = STATS_CATEGORY_TO_DIR["event"]
usage_dir = STATS_CATEGORY_TO_DIR["usage"]
# ---
self._shutdown = False
self._providers: List[StatisticsProvider] = []
self._outbox = StatisticsUploader()
self._timer = DTReminder(frequency=FREQUENCY.EVERY_MINUTE)
# register providers
# - stats/events/ dir
self._providers.extend(glob_event_providers(events_dir, "*.json"))
# - stats/usage/ dirs
self._providers.extend(
glob_usage_providers(os.path.join(usage_dir, "disk_image"),
"*.json", "disk_image"))
self._providers.extend(
glob_usage_providers(os.path.join(usage_dir, "init_sd_card"),
"*.json", "init_sd_card"))
# - docker/ps
self._providers.append(DockerPSProvider(FREQUENCY.EVERY_MINUTE))
# - docker/images
self._providers.append(DockerImagesProvider(FREQUENCY.EVERY_MINUTE))
# - uptime
self._providers.append(UptimeProvider(FREQUENCY.EVERY_30_MINUTES))
# - network/configuration
self._providers.append(
NetworkConfigurationProvider(FREQUENCY.EVERY_1_HOUR))
# - ros/graph
self._providers.append(ROSGraphProvider(FREQUENCY.EVERY_30_MINUTES))
# - health
self._providers.append(HealthProvider(FREQUENCY.EVERY_30_MINUTES))
# - network/public_ip
self._providers.append(PublicIPProvider(FREQUENCY.ONESHOT))
# - geolocation
self._providers.append(GeolocationProvider(FREQUENCY.ONESHOT))
# - battery/history
self._providers.append(BatteryHistoryProvider(FREQUENCY.EVERY_2_HOURS))
# - battery/info
self._providers.append(BatteryInfoProvider(FREQUENCY.ONESHOT))
# - lsusb
self._providers.append(LSUSBProvider(FREQUENCY.EVERY_2_HOURS))
# - wireless/status
self._providers.append(
WirelessStatusProvider(FREQUENCY.EVERY_30_MINUTES))
# - robot/hostname
self._providers.append(RobotHostnameProvider())
# - robot/type
self._providers.append(RobotTypeProvider())
# - robot/configuration
self._providers.append(RobotConfigurationProvider())
# launch outbox
self._outbox.start()
def is_shutdown(self) -> bool:
return self._shutdown
def shutdown(self):
self._outbox.shutdown()
self._shutdown = True
def run(self):
app = DTProcess.get_instance()
# (try to) read the device ID
try:
device_id = get_device_id()
except ValueError:
# no device ID? nothing to do
app.logger.warning(
"Could not find the device's unique ID. Cannot share stats.")
return
# this process gets data from a bunch of stats providers and places them in the outbox
while not app.is_shutdown():
# don't do this constantly
if not self._timer.is_time():
time.sleep(1)
continue
# temporary structures
to_remove = []
# go through the providers
for provider in self._providers:
if provider.istime:
# get timestamp and payload
stamp, payload = provider.data
if stamp is None or payload is None:
continue
# format payload
payload = provider.format(payload)
# pack data into a point
point = StatisticsPoint(category=StatisticsCategory(
provider.category),
key=provider.key,
device=device_id,
stamp=stamp,
payload=payload,
provider=provider)
# add point to outbox
self._outbox.add(point)
# remove exhausted providers
if provider.one_shot:
to_remove.append(provider)
# remove providers
self._providers = list(
filter(lambda p: p not in to_remove, self._providers))
class RectifierNode(DTROS):
def __init__(self, node_name):
super().__init__(node_name, node_type=NodeType.PERCEPTION)
# parameters
self.publish_freq = DTParam("~publish_freq", -1)
self.alpha = DTParam("~alpha", 0.0)
# utility objects
self.jpeg = TurboJPEG()
self.reminder = DTReminder(frequency=self.publish_freq.value)
self.camera_model = None
self.rect_camera_info = None
self.mapx, self.mapy = None, None
# subscribers
self.sub_img = rospy.Subscriber("~image_in",
CompressedImage,
self.cb_image,
queue_size=1,
buff_size="10MB")
self.sub_camera_info = rospy.Subscriber("~camera_info_in",
CameraInfo,
self.cb_camera_info,
queue_size=1)
# publishers
self.pub_img = rospy.Publisher(
"~image/compressed",
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help=
"Rectified image (i.e., image with no distortion effects from the lens).",
)
self.pub_camera_info = rospy.Publisher(
"~camera_info",
CameraInfo,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION,
dt_healthy_freq=self.publish_freq.value,
dt_help="Camera parameters for the (virtual) rectified camera.",
)
def cb_camera_info(self, msg):
# unsubscribe from camera_info
self.loginfo(
"Camera info message received. Unsubscribing from camera_info topic."
)
# noinspection PyBroadException
try:
self.sub_camera_info.shutdown()
except BaseException:
pass
# ---
H, W = msg.height, msg.width
# create new camera info
self.camera_model = PinholeCameraModel()
self.camera_model.fromCameraInfo(msg)
# find optimal rectified pinhole camera
with self.profiler("/cb/camera_info/get_optimal_new_camera_matrix"):
rect_camera_K, _ = cv2.getOptimalNewCameraMatrix(
self.camera_model.K, self.camera_model.D, (W, H),
self.alpha.value)
# create rectification map
with self.profiler("/cb/camera_info/init_undistort_rectify_map"):
self.mapx, self.mapy = cv2.initUndistortRectifyMap(
self.camera_model.K, self.camera_model.D, None, rect_camera_K,
(W, H), cv2.CV_32FC1)
# pack rectified camera info into a CameraInfo message
self.rect_camera_info = CameraInfo(
width=W,
height=H,
K=rect_camera_K.flatten().tolist(),
R=np.eye(3).flatten().tolist(),
P=np.zeros((3, 4)).flatten().tolist(),
)
def cb_image(self, msg):
# make sure this matters to somebody
if not self.pub_img.anybody_listening(
) and not self.pub_camera_info.anybody_listening():
return
# make sure we have a map to use
if self.mapx is None or self.mapy is None:
return
# make sure the node is not switched off
if not self.switch:
return
# make sure this is a good time to publish (always keep this as last check)
if not self.reminder.is_time(frequency=self.publish_freq.value):
return
# turn 'compressed distorted image message' into 'raw distorted image'
with self.profiler("/cb/image/decode"):
dist_img = self.jpeg.decode(msg.data)
# run input image through the lens map
with self.profiler("/cb/image/rectify"):
rect_img = cv2.remap(dist_img, self.mapx, self.mapy,
cv2.INTER_NEAREST)
# turn 'raw rectified image' into 'compressed rectified image message'
with self.profiler("/cb/image/encode"):
# rect_img_msg = self.bridge.cv2_to_compressed_imgmsg(rect_img)
rect_img_msg = CompressedImage(format="jpeg",
data=self.jpeg.encode(rect_img))
# maintain original header
rect_img_msg.header.stamp = msg.header.stamp
rect_img_msg.header.frame_id = msg.header.frame_id
self.rect_camera_info.header.stamp = msg.header.stamp
self.rect_camera_info.header.frame_id = msg.header.frame_id
# publish image
self.pub_img.publish(rect_img_msg)
# publish camera info
self.pub_camera_info.publish(self.rect_camera_info)
class DistributedTFNode(DTROS):
PUBLISH_TF_STATIC_EVERY_SECS = 2
def __init__(self):
super(DistributedTFNode,
self).__init__(node_name='distributed_tf_node',
node_type=NodeType.SWARM)
# get static parameters
self.robot_hostname = rospy.get_param('~veh')
self.map_name = _sanitize_hostname(rospy.get_param('~map'))
self.tag_id = rospy.get_param('~tag_id')
self.min_distance_odom = rospy.get_param('~min_distance_odom')
self.max_time_between_poses = rospy.get_param(
'~max_time_between_poses')
# define local reference frames' names
self._tag_mount = f'{self.robot_hostname}/tag_mount'
self._footprint_frame = f'{self.robot_hostname}/footprint'
# create communication group
self._group = DTCommunicationGroup("/autolab/tf", AutolabTransform)
# create static tfs holder and access semaphore
self._static_tfs = {}
self._static_tfs_sem = threading.Semaphore(1)
self._tf_buffer = tf2_ros.Buffer()
self._tf_listener = tf2_ros.TransformListener(self._tf_buffer)
# create publishers
self._tf_pub = self._group.Publisher()
# fetch/publish right away and then set timers
if self.tag_id != '__NOTSET__':
threading.Thread(target=self._fetch_tag_tf).start()
self._pub_timer = rospy.Timer(
rospy.Duration(self.PUBLISH_TF_STATIC_EVERY_SECS),
self._publish_static_tfs)
# setup subscribers for odometry
self._odo_sub = rospy.Subscriber("~odometry_in",
Odometry,
self._cb_odometry,
queue_size=1)
self._pose_last = None
self._reminder = DTReminder(frequency=10)
def on_shutdown(self):
if hasattr(self, '_group') and self._group is not None:
self._group.shutdown()
def _fetch_tag_tf(self, *_):
origin = self._tag_mount
target = self._footprint_frame
# try to fetch the TF
while not self.is_shutdown:
try:
self.loginfo(f"Looking for TF[{origin}] -> [{target}]...")
transform = self._tf_buffer.lookup_transform(
origin, target, rospy.Time())
tf = AutolabTransform(
origin=AutolabReferenceFrame(
time=transform.header.stamp,
type=AutolabReferenceFrame.TYPE_DUCKIEBOT_TAG,
# NOTE: fetch TF /tag_frame -> /footprint but publish tag/XYZ -> /footprint
name=f'tag/{self.tag_id}',
robot=self.robot_hostname),
target=AutolabReferenceFrame(
time=transform.header.stamp,
type=AutolabReferenceFrame.TYPE_DUCKIEBOT_FOOTPRINT,
name=target,
robot=self.robot_hostname),
is_fixed=True,
is_static=False,
transform=transform.transform)
# add TF to the list of TFs to publish
self._static_tfs_sem.acquire()
try:
self._static_tfs[(origin, target)] = tf
finally:
self._static_tfs_sem.release()
self.loginfo(
f"Found TF[{origin}] -> [{target}]. Stopping TF listener thread."
)
return
except (tf2_ros.LookupException, tf2_ros.ExtrapolationException):
self.logwarn(
f"Could not find a static TF [{origin}] -> [{target}]")
except tf2_ros.ConnectivityException:
pass
time.sleep(2)
def _publish_static_tfs(self, *_):
tfs = []
self._static_tfs_sem.acquire()
try:
for transform in self._static_tfs.values():
tfs.append(transform)
finally:
self._static_tfs_sem.release()
# publish
for tf in tfs:
self._tf_pub.publish(tf, destination=self.map_name)
def _cb_odometry(self, pose_now):
if self._pose_last is None:
self._pose_last = pose_now
return
if not self._reminder.is_time():
return
# Only add the transform if the new pose is sufficiently different
t_now_to_world = np.array([
pose_now.pose.pose.position.x, pose_now.pose.pose.position.y,
pose_now.pose.pose.position.z
])
t_last_to_world = np.array([
self._pose_last.pose.pose.position.x,
self._pose_last.pose.pose.position.y,
self._pose_last.pose.pose.position.z
])
o = pose_now.pose.pose.orientation
q_now_to_world = np.array([o.x, o.y, o.z, o.w])
o = self._pose_last.pose.pose.orientation
q_last_to_world = np.array([o.x, o.y, o.z, o.w])
q_world_to_last = q_last_to_world
q_world_to_last[3] *= -1
q_now_to_last = tr.quaternion_multiply(q_world_to_last, q_now_to_world)
world_to_last = np.matrix(tr.quaternion_matrix(q_world_to_last))
#now_to_last = np.matrix(tr.quaternion_matrix(q_now_to_last))
# print(now_to_last)
#now_to_last = now_to_last[0:3][:, 0:3]
R_world_to_last = world_to_last[0:3][:, 0:3]
# print(now_to_last)
#t_now_to_last = np.array(np.dot(now_to_last, t_now_to_world - t_last_to_world))
t_now_to_last = np.array(
np.dot(R_world_to_last, t_now_to_world - t_last_to_world))
t_now_to_last = t_now_to_last.flatten()
# compute TF between `pose_now` and `pose_last`
transform = Transform(translation=Vector3(x=t_now_to_last[0],
y=t_now_to_last[1],
z=t_now_to_last[2]),
rotation=Quaternion(x=q_now_to_last[0],
y=q_now_to_last[1],
z=q_now_to_last[2],
w=q_now_to_last[3]))
# pack TF into an AutolabTransform message
tf = AutolabTransform(
origin=AutolabReferenceFrame(
time=self._pose_last.header.stamp,
type=AutolabReferenceFrame.TYPE_DUCKIEBOT_FOOTPRINT,
name=self._footprint_frame,
robot=self.robot_hostname),
target=AutolabReferenceFrame(
time=pose_now.header.stamp,
type=AutolabReferenceFrame.TYPE_DUCKIEBOT_FOOTPRINT,
name=self._footprint_frame,
robot=self.robot_hostname),
is_fixed=False,
is_static=False,
transform=transform)
# publish
self._tf_pub.publish(tf, destination=self.map_name)
# update last pose
self._pose_last = pose_now
class AprilTagDetector(DTROS):
def __init__(self):
super(AprilTagDetector,
self).__init__(node_name='apriltag_detector_node',
node_type=NodeType.PERCEPTION)
# get static parameters
self.family = rospy.get_param('~family', 'tag36h11')
self.nthreads = rospy.get_param('~nthreads', 1)
self.quad_decimate = rospy.get_param('~quad_decimate', 1.0)
self.quad_sigma = rospy.get_param('~quad_sigma', 0.0)
self.refine_edges = rospy.get_param('~refine_edges', 1)
self.decode_sharpening = rospy.get_param('~decode_sharpening', 0.25)
self.tag_size = rospy.get_param('~tag_size', 0.065)
# dynamic parameter
self.detection_freq = DTParam('~detection_freq',
default=-1,
param_type=ParamType.INT,
min_value=-1,
max_value=30)
self._detection_reminder = DTReminder(
frequency=self.detection_freq.value)
# camera info
self._camera_parameters = None
self._camera_frame = None
# create detector object
self._at_detector = Detector(families=self.family,
nthreads=self.nthreads,
quad_decimate=self.quad_decimate,
quad_sigma=self.quad_sigma,
refine_edges=self.refine_edges,
decode_sharpening=self.decode_sharpening)
# create a CV bridge object
self._bridge = CvBridge()
# create subscribers
self._img_sub = rospy.Subscriber('image_rect', Image, self._img_cb)
self._cinfo_sub = rospy.Subscriber('camera_info', CameraInfo,
self._cinfo_cb)
# create publishers
self._img_pub = rospy.Publisher('tag_detections_image/compressed',
CompressedImage,
queue_size=1,
dt_topic_type=TopicType.VISUALIZATION)
self._tag_pub = rospy.Publisher('tag_detections',
AprilTagDetectionArray,
queue_size=1,
dt_topic_type=TopicType.PERCEPTION)
self._img_pub_busy = False
# create TF broadcaster
self._tf_bcaster = tf.TransformBroadcaster()
# spin forever
rospy.spin()
def _img_cb(self, data):
if self._camera_parameters is None:
return
if not self._detection_reminder.is_time(
frequency=self.detection_freq.value):
return
# ---
# turn image message into grayscale image
img = self._bridge.imgmsg_to_cv2(data, desired_encoding='mono8')
# detect tags
tags = self._at_detector.detect(img, True, self._camera_parameters,
self.tag_size)
# draw the detections on an image (if needed)
if self._img_pub.anybody_listening() and not self._img_pub_busy:
self._img_pub_busy = True
Thread(target=self._publish_detections_image,
args=(img, tags)).start()
# pack detections into a message
msg = AprilTagDetectionArray()
detection_time = rospy.Time.now()
msg.header.stamp = detection_time
msg.header.frame_id = self._camera_frame
for tag in tags:
# turn rotation matrix into quaternion
q = _matrix_to_quaternion(tag.pose_R)
p = tag.pose_t.T[0]
# create single tag detection object
detection = AprilTagDetection(
transform=Transform(translation=Vector3(x=p[0], y=p[1],
z=p[2]),
rotation=Quaternion(x=q[0],
y=q[1],
z=q[2],
w=q[3])),
tag_id=tag.tag_id,
tag_family=str(tag.tag_family),
hamming=tag.hamming,
decision_margin=tag.decision_margin,
homography=tag.homography.flatten().astype(
np.float32).tolist(),
center=tag.center.tolist(),
corners=tag.corners.flatten().tolist(),
pose_error=tag.pose_err)
# add detection to array
msg.detections.append(detection)
# publish tf
self._tf_bcaster.sendTransform(p.tolist(), q.tolist(),
detection_time,
'/tag{:s}'.format(str(tag.tag_id)),
self._camera_frame)
# publish detections
self._tag_pub.publish(msg)
# update healthy frequency metadata
self._tag_pub.set_healthy_freq(self._img_sub.get_frequency())
self._img_pub.set_healthy_freq(self._img_sub.get_frequency())
def _publish_detections_image(self, img, tags):
# get a color buffer from the BW image
color_img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
# draw each tag
for tag in tags:
for idx in range(len(tag.corners)):
cv2.line(color_img, tuple(tag.corners[idx - 1, :].astype(int)),
tuple(tag.corners[idx, :].astype(int)), (0, 255, 0))
# draw the tag ID
cv2.putText(color_img,
str(tag.tag_id),
org=(tag.corners[0, 0].astype(int) + 10,
tag.corners[0, 1].astype(int) + 10),
fontFace=cv2.FONT_HERSHEY_SIMPLEX,
fontScale=0.8,
color=(0, 0, 255))
# pack image into a message
img_msg = self._bridge.cv2_to_compressed_imgmsg(color_img)
# ---
self._img_pub.publish(img_msg)
self._img_pub_busy = False
def _cinfo_cb(self, data):
K = np.array(data.K).reshape((3, 3))
self._camera_parameters = (K[0, 0], K[1, 1], K[0, 2], K[1, 2])
self._camera_frame = data.header.frame_id
# once we got the camera info, we can stop the subscriber
self._cinfo_sub.shutdown()