def bayes2spencer(self, bayes_msg):
spencer_msg = TrackedPersons()
spencer_msg.header = bayes_msg.header
for i, pose in enumerate(bayes_msg.poses):
track = TrackedPerson()
track.track_id = self.string2uint64(bayes_msg.uuids[i])
# PoseWithCovariance
track.pose.pose.position = pose.position
track.pose.pose.orientation = pose.orientation
# TwistWithCovariance
track.twist.twist.linear = bayes_msg.velocities[i]
# Data not in bayes. Not sure about these ...
track.pose.covariance = (np.random.normal(0.3, 0.1) *
np.identity(6)).flatten().tolist()
track.twist.covariance = (np.random.normal(0.3, 0.1) *
np.identity(6)).flatten().tolist()
# we assume 0 here
# track.twist.twist.angular
track.is_occluded = False
track.is_matched = False
track.detection_id = self.string2uint64(bayes_msg.uuids[i])
track.age = 0
spencer_msg.tracks.append(track)
return spencer_msg
def detectedPersonsCallback(trackAssociation, detectedPersons,
syncronized_person_pub):
age = rospy.Time.now() - detectedPersons.header.stamp
output = "New detections with track association available (age of detections = %.2f sec)! Detection to track association: " % age.to_sec(
)
syncronizedPersons = TrackedPersons()
syncronizedPersons.header = detectedPersons.header
if detectedPersons.detections:
for detectedPerson in detectedPersons.detections:
# The TrackSynchronizer invoking this callback guarantees that the detectedPersons message is buffered until a
# track association is available for these detections (by comparing message timestamps of tracks and detections).
detectionId = detectedPerson.detection_id
trackId = trackAssociation.lookupTrackId(
detectionId) # <-- this is what this is all about
output += "\n[det %d --> track %s]" % (detectionId, str(trackId))
if trackId is not None:
syncronizedPerson = TrackedPerson()
syncronizedPerson.track_id = trackId
syncronizedPerson.detection_id = detectionId
syncronizedPersons.tracks.append(syncronizedPerson)
rospy.loginfo(output)
if len(syncronizedPersons.tracks) > 0:
syncronized_person_pub.publish(syncronizedPersons)
else:
output += "Empty set of detections!"
def main():
# Main code
trackPublisher = rospy.Publisher('/spencer/perception/tracked_persons',
TrackedPersons, queue_size=1)
rospy.init_node('mock_tracks')
rate = rospy.Rate(10)
seqCounter = 0
while not rospy.is_shutdown():
trackedPersons = TrackedPersons()
trackedPersons.header.seq = seqCounter
trackedPersons.header.frame_id = "odom"
trackedPersons.header.stamp = rospy.Time.now()
# trackedPersons.tracks.append(
# createTrackedPerson( trackId, x, y, theta ) )
trackedPersons.tracks.append(createTrackedPerson(1, 6.1, 4, 181))
trackedPersons.tracks.append(createTrackedPerson(2, 6, 5.1, 168.7))
trackedPersons.tracks.append(createTrackedPerson(3, 7, 7, 182))
trackedPersons.tracks.append(createTrackedPerson(4, 6.8, 8.0, -168.7))
trackedPersons.tracks.append(createTrackedPerson(5, 6.2, 8.7, -168.3))
# some two loners
trackedPersons.tracks.append(createTrackedPerson(6, 12.2, 11.7, 68.3))
trackedPersons.tracks.append(createTrackedPerson(7, 12.1, 8.7, -45))
trackPublisher.publish(trackedPersons)
seqCounter += 1
rate.sleep()
def main():
# Main code
trackPublisher = rospy.Publisher('/spencer/perception/tracked_persons',
TrackedPersons)
#obstaclesPublisher = rospy.Publisher('/pedsim/static_obstacles', GridCells )
rospy.init_node('mock_tracked_persons')
rate = rospy.Rate(10)
#obstacles = yaml.load(OBSTACLE_YAML)
#obstacles = [ d for d in obstacles]
seqCounter = 0
while not rospy.is_shutdown():
trackedPersons = TrackedPersons()
trackedPersons.header.seq = seqCounter
trackedPersons.header.frame_id = "odom"
trackedPersons.header.stamp = rospy.Time.now()
#trackedPersons.tracks.append( createTrackedPerson( trackId, x, y, theta ) )
trackedPersons.tracks.append(createTrackedPerson(1, 2, 5, 270))
trackedPersons.tracks.append(createTrackedPerson(2, 5, 3.5, 109))
trackedPersons.tracks.append(createTrackedPerson(3, 6, 5, 90))
trackedPersons.tracks.append(createTrackedPerson(4, 5, 7.2, 109))
trackedPersons.tracks.append(
createTrackedPerson(5, 9.2, 1.2, 71.56 - 90))
trackedPersons.tracks.append(
createTrackedPerson(6, 7.1, 2.5, 80.9097 - 90))
trackedPersons.tracks.append(createTrackedPerson(7, 8.2, 7.6, 8))
trackedPersons.tracks.append(createTrackedPerson(8, 7.1, 6.5, 10))
trackedPersons.tracks.append(
createTrackedPerson(9, 2.2, 1.8, 85.2364 - 90))
trackedPersons.tracks.append(
createTrackedPerson(10, 4.1, 1.9, 93.8141 - 90))
trackedPersons.tracks.append(
createTrackedPerson(11, 1.7, 9.3, 78.6901 - 90))
trackedPersons.tracks.append(
createTrackedPerson(12, 2.2, 7.5, 63.4349 - 90))
trackPublisher.publish(trackedPersons)
#obstacles['header'] = trackedPersons.header
#obstaclesPublisher.publish( obstacles )
seqCounter += 1
rate.sleep()
def main():
# Main code
trackPublisher = rospy.Publisher('/spencer/perception/tracked_persons',
TrackedPersons)
rospy.init_node('mocktracks_info_screen')
rate = rospy.Rate(10)
seqCounter = 0
while not rospy.is_shutdown():
trackedPersons = TrackedPersons()
trackedPersons.header.seq = seqCounter
trackedPersons.header.frame_id = "odom"
trackedPersons.header.stamp = rospy.Time.now()
# trackedPersons.tracks.append(
# createTrackedPerson( trackId, x, y, theta ) )
trackedPersons.tracks.append(createTrackedPerson(1, 3, 7, 270))
trackedPersons.tracks.append(createTrackedPerson(2, 7, 5.5, 109))
trackedPersons.tracks.append(createTrackedPerson(3, 8, 6.5, 90))
trackedPersons.tracks.append(createTrackedPerson(4, 7, 9.2, 109))
trackedPersons.tracks.append(createTrackedPerson(5, 7.5, 8.0, 109))
# trackedPersons.tracks.append(
# createTrackedPerson(5, 9.2, 1.2, 71.56 - 90))
# trackedPersons.tracks.append(
# createTrackedPerson(6, 7.1, 2.5, 80.9097 - 90))
# trackedPersons.tracks.append(createTrackedPerson(7, 8.2, 7.6, 8))
# trackedPersons.tracks.append(createTrackedPerson(8, 7.1, 6.5, 10))
# trackedPersons.tracks.append(
# createTrackedPerson(9, 2.2, 1.8, 85.2364 - 90))
# trackedPersons.tracks.append(
# createTrackedPerson(10, 4.1, 1.9, 93.8141 - 90))
# trackedPersons.tracks.append(
# createTrackedPerson(11, 1.7, 9.3, 78.6901 - 90))
# trackedPersons.tracks.append(
# createTrackedPerson(12, 2.2, 7.5, 63.4349 - 90))
trackPublisher.publish(trackedPersons)
seqCounter += 1
rate.sleep()
def publish(self, trackedPersons, humanAttributes):
humanAttributes.header = trackedPersons.header
self.trackedPersonPublisher.publish(trackedPersons)
self.humanAttributePublisher.publish(humanAttributes)
# Separately publish the currently active track in the editor, if any
if self.trackedPersonWithoutActivePublisher.get_num_connections(
) > 0 or self.activeTrackedPersonPublisher.get_num_connections() > 0:
activeTrackedPersons = TrackedPersons()
activeTrackedPersons.header = trackedPersons.header
trackedPersonsWithoutActive = TrackedPersons()
trackedPersonsWithoutActive.header = trackedPersons.header
for trackedPerson in trackedPersons.tracks:
if self.editor is None or trackedPerson.track_id != self.editor.activeTrackId:
trackedPersonsWithoutActive.tracks.append(trackedPerson)
else:
activeTrackedPersons.tracks.append(trackedPerson)
self.activeTrackedPersonPublisher.publish(activeTrackedPersons)
self.trackedPersonWithoutActivePublisher.publish(
trackedPersonsWithoutActive)
def main():
# Main code
trackPublisher = rospy.Publisher('/spencer/perception/tracked_persons',
TrackedPersons)
#obstaclesPublisher = rospy.Publisher('/pedsim/static_obstacles', GridCells )
rospy.init_node('mock_tracked_persons')
rate = rospy.Rate(10)
#obstacles = yaml.load(OBSTACLE_YAML)
#obstacles = [ d for d in obstacles]
seqCounter = 0
while not rospy.is_shutdown():
trackedPersons = TrackedPersons()
trackedPersons.header.seq = seqCounter
trackedPersons.header.frame_id = "odom"
trackedPersons.header.stamp = rospy.Time.now()
#trackedPersons.tracks.append( createTrackedPerson( trackId, x, y, theta ) )
trackedPersons.tracks.append(createTrackedPerson(01, 5, 4, 90))
trackedPersons.tracks.append(createTrackedPerson(02, 6, 5.45878, 90))
trackedPersons.tracks.append(createTrackedPerson(03, 7.22, 5.70, 90))
trackedPersons.tracks.append(
createTrackedPerson(04, 2 + 7.22, 7.33, 90))
trackedPersons.tracks.append(
createTrackedPerson(05, 2 + 8.92, 8.42, 90))
trackedPersons.tracks.append(
createTrackedPerson(06, 2 + 7.92, 10.41, 90))
trackedPersons.tracks.append(createTrackedPerson(
07, 2 + 7.2, 9.44, 90))
trackedPersons.tracks.append(createTrackedPerson(8, 2 + 7, 14 - 2, 90))
trackedPersons.tracks.append(
createTrackedPerson(9, 2 + 6, 15.4123 - 2, 90))
trackedPersons.tracks.append(
createTrackedPerson(10, 5 - 1, 18.595 - 5, 280))
trackedPersons.tracks.append(
createTrackedPerson(11, 5 - 1, 20 - 5, 270))
trackedPersons.tracks.append(
createTrackedPerson(12, 6 - 1, 21.5491 - 5, 240))
trackedPersons.tracks.append(
createTrackedPerson(13, 7.48044 - 1, 19 - 5, 90))
trackedPersons.tracks.append(createTrackedPerson(14, 6, 24.5463, 45))
trackedPersons.tracks.append(createTrackedPerson(15, 8, 28, 90))
trackedPersons.tracks.append(createTrackedPerson(16, 10.4458, 23, 68))
trackedPersons.tracks.append(createTrackedPerson(17, 11.5004, 27, 88))
trackedPersons.tracks.append(createTrackedPerson(18, 14, 25.4389, 20))
trackedPersons.tracks.append(createTrackedPerson(19, 15, 21, 90))
trackedPersons.tracks.append(createTrackedPerson(20, 15, 22.4308, 92))
trackedPersons.tracks.append(createTrackedPerson(21, 15.4676, 24, 91))
trackedPersons.tracks.append(
createTrackedPerson(22, 16.5423, 25.4178, 90))
trackedPersons.tracks.append(createTrackedPerson(23, 18, 20, 90))
trackedPersons.tracks.append(
createTrackedPerson(24, 18.5532, 21.5011, 90))
trackedPersons.tracks.append(
createTrackedPerson(25, 15.4739, 16.5314, 45))
trackedPersons.tracks.append(createTrackedPerson(26, 20, 25.5746, 90))
trackedPersons.tracks.append(createTrackedPerson(27, 21.5327, 24, 90))
trackedPersons.tracks.append(createTrackedPerson(28, 22, 26.4632, 90))
trackedPersons.tracks.append(createTrackedPerson(29, 21, 18, 45))
trackedPersons.tracks.append(createTrackedPerson(30, 23, 20.4335, 90))
trackedPersons.tracks.append(
createTrackedPerson(31, 23.4972, 21.4055, 90))
trackedPersons.tracks.append(
createTrackedPerson(32, 23.4025, 22.4749, 90))
trackedPersons.tracks.append(
createTrackedPerson(33, 24.5281, 18.5868, 54))
trackedPersons.tracks.append(
createTrackedPerson(34, 16.554, 3.40568 - 2, 94))
trackedPersons.tracks.append(createTrackedPerson(35, 16, 6 - 1, 94))
trackedPersons.tracks.append(createTrackedPerson(36, 20, 4, 0))
trackedPersons.tracks.append(createTrackedPerson(37, 19, 12, 25))
trackedPersons.tracks.append(createTrackedPerson(38, 23, 8, 50))
trackedPersons.tracks.append(createTrackedPerson(39, 24, 10, 90))
trackedPersons.tracks.append(createTrackedPerson(40, 25, 12, 120))
trackedPersons.tracks.append(createTrackedPerson(41, 7.51, 22.41, 80))
trackedPersons.tracks.append(createTrackedPerson(42, 8.21, 25.7, 81))
trackedPersons.tracks.append(createTrackedPerson(43, 3.31, 27.7, 81))
trackedPersons.tracks.append(createTrackedPerson(44, 11.421, 18.7, 75))
trackedPersons.tracks.append(createTrackedPerson(45, 25.21, 27.0, 85))
trackedPersons.tracks.append(createTrackedPerson(46, 18.23, 6.87, -91))
trackedPersons.tracks.append(createTrackedPerson(47, 18.6, 8.90, -90))
trackedPersons.tracks.append(createTrackedPerson(48, 20.4, 7.87, 85))
trackedPersons.tracks.append(createTrackedPerson(
49, 15.684, 10.74, 75))
trackedPersons.tracks.append(createTrackedPerson(50, 15.72, 14.51, 70))
trackPublisher.publish(trackedPersons)
#obstacles['header'] = trackedPersons.header
#obstaclesPublisher.publish( obstacles )
seqCounter += 1
rate.sleep()
def do_3d_tracking(self, detections_2d, detections_3d):
start = time.time()
#rospy.loginfo("Tracking frame")
# convert_detections
boxes_2d = []
boxes_3d = []
valid_3d = []
features_2d = []
features_3d = []
dets_2d = sorted(detections_2d.detection2d_with_features,
key=lambda x: x.frame_det_id)
dets_3d = sorted(detections_3d.detection3d_with_features,
key=lambda x: x.frame_det_id)
i, j = 0, 0
while i < len(dets_2d) and j < len(dets_3d):
det_2d = dets_2d[i]
det_3d = dets_3d[j]
if det_2d.frame_det_id == det_3d.frame_det_id:
i += 1
j += 1
valid_3d.append(det_3d.valid)
boxes_2d.append(
np.array([
det_2d.x1, det_2d.y1, det_2d.x2, det_2d.y2, 1, -1, -1
]))
features_2d.append(torch.Tensor(det_2d.feature).to('cuda:0'))
if det_3d.valid:
boxes_3d.append(
np.array([
det_3d.x, det_3d.y, det_3d.z, det_3d.l, det_3d.h,
det_3d.w, det_3d.theta
]))
features_3d.append(
torch.Tensor(det_3d.feature).to('cuda:0'))
else:
boxes_3d.append(None)
features_3d.append(None)
elif det_2d.frame_det_id < det_3d.frame_det_id:
i += 1
else:
j += 1
if not boxes_3d:
boxes_3d = None
features_3d, features_2d = combine_features(
features_2d,
features_3d,
valid_3d,
self.combination_model,
depth_weight=self.depth_weight)
detections = convert_detections(boxes_2d, features_3d, features_2d,
boxes_3d)
self.tracker.predict()
self.tracker.update(None, detections)
tracked_array = TrackedPersons()
tracked_array.header.stamp = detections_3d.header.stamp
tracked_array.header.frame_id = 'occam'
for track in self.tracker.tracks:
if not track.is_confirmed():
continue
#print('Confirmed track!')
pose_msg = Pose()
tracked_person_msg = TrackedPerson()
tracked_person_msg.header.stamp = detections_3d.header.stamp
tracked_person_msg.header.frame_id = 'occam'
tracked_person_msg.track_id = track.track_id
if track.time_since_update < 2:
tracked_person_msg.is_matched = True
else:
tracked_person_msg.is_matched = False
bbox = track.to_tlwh3d()
covariance = track.get_cov().reshape(-1).tolist()
pose_msg.position.x = bbox[0]
pose_msg.position.y = bbox[1] - bbox[4] / 2
pose_msg.position.z = bbox[2]
pose_msg = PoseWithCovariance(pose=pose_msg, covariance=covariance)
tracked_person_msg.pose = pose_msg
tracked_array.tracks.append(tracked_person_msg)
self.tracker_output_pub.publish(tracked_array)
def newSegmentationReceived(self, laserscan, laserscanSegmentation):
currentStamp = laserscanSegmentation.header.stamp
pointCount = len(laserscan.ranges)
cartesianCoordinates = []
# Required for velocity calculations
if self._lastDataStamp is None:
self._lastDataStamp = laserscanSegmentation.header.stamp
# Build lookup of cartesian coordinates per laser point
for pointIndex in xrange(0, pointCount):
cartesianCoordinates.append(
self.calculateCartesianCoordinates(laserscan, pointIndex))
# For each labelled segment, create and append one TrackedPerson and DetectedPerson message
trackedPersons = TrackedPersons(header=laserscanSegmentation.header)
detectedPersons = DetectedPersons(header=laserscanSegmentation.header)
for segment in laserscanSegmentation.segments:
# Calculate centroid of tracked person
centroid = numpy.array([0.0, 0.0, 0.0])
for pointIndex in segment.measurement_indices:
centroid += cartesianCoordinates[pointIndex]
centroid /= float(len(segment.measurement_indices))
# Lookup previous centroid (for velocity/twist calculation), assume zero velocity at track initialization
if not segment.label in self._previousCentroidLookup:
self._previousCentroidLookup[
segment.label] = collections.deque()
# Maintain centroid history
centroidHistory = self._previousCentroidLookup[segment.label]
while len(centroidHistory) > 20:
centroidHistory.popleft()
# Calculate average velocity over past few frames
dt = 0
velocity = accumulatedVelocity = numpy.array([0.0, 0.0, 0.0])
if centroidHistory:
previousCentroid = centroid
previousStamp = currentStamp
for historyStamp, historyCentroid in reversed(centroidHistory):
accumulatedVelocity += previousCentroid - historyCentroid
dt += abs((previousStamp - historyStamp).to_sec())
previousCentroid = historyCentroid
previousStamp = historyStamp
velocity = accumulatedVelocity / dt
centroidHistory.append((currentStamp, centroid))
# Remember age of track
if not segment.label in self._firstTrackEncounterLookup:
self._firstTrackEncounterLookup[segment.label] = currentStamp
# Initialize TrackedPerson message
trackedPerson = TrackedPerson()
trackedPerson.track_id = segment.label
trackedPerson.age = currentStamp - self._firstTrackEncounterLookup[
segment.label]
trackedPerson.detection_id = self._detectionIdCounter
trackedPerson.is_occluded = False
# Set position
LARGE_VARIANCE = 99999999
trackedPerson.pose.pose.position.x = centroid[0]
trackedPerson.pose.pose.position.y = centroid[1]
trackedPerson.pose.pose.position.z = centroid[2]
# Set orientation
if dt > 0:
yaw = math.atan2(velocity[1], velocity[0])
quaternion = tf.transformations.quaternion_from_euler(
0, 0, yaw)
trackedPerson.pose.pose.orientation = Quaternion(
x=quaternion[0],
y=quaternion[1],
z=quaternion[2],
w=quaternion[3])
trackedPerson.pose.covariance[
2 * 6 + 2] = trackedPerson.pose.covariance[
3 * 6 + 3] = trackedPerson.pose.covariance[
4 * 6 + 4] = LARGE_VARIANCE # z pos, roll, pitch
# Set velocity
if dt > 0:
trackedPerson.twist.twist.linear.x = velocity[0]
trackedPerson.twist.twist.linear.y = velocity[1]
trackedPerson.twist.twist.linear.z = velocity[2]
trackedPerson.twist.covariance[
2 * 6 + 2] = trackedPerson.twist.covariance[
3 * 6 + 3] = trackedPerson.twist.covariance[
4 * 6 + 4] = trackedPerson.twist.covariance[
5 * 6 +
5] = LARGE_VARIANCE # linear z, angular x, y, z
# Append to list of tracked persons
trackedPersons.tracks.append(trackedPerson)
# Initialize DetectedPerson message by copying data from TrackedPerson
detectedPerson = DetectedPerson()
detectedPerson.detection_id = trackedPerson.detection_id
detectedPerson.confidence = 1.0
detectedPerson.pose = copy.deepcopy(trackedPerson.pose)
detectedPerson.pose.pose.orientation = Quaternion()
for i in xrange(0, 2):
detectedPerson.pose.covariance[i * 6 + i] = 0.17 * 0.17
detectedPerson.pose.covariance[5 * 6 + 5] = LARGE_VARIANCE # yaw
detectedPersons.detections.append(detectedPerson)
self._detectionIdCounter += 1
# Publish tracked persons
self.trackedPersonsPublisher.publish(trackedPersons)
self.detectedPersonsPublisher.publish(detectedPersons)
self._lastDataStamp = laserscanSegmentation.header.stamp
def main():
# Main code
trackPublisher = rospy.Publisher('/spencer/perception/tracked_persons',
TrackedPersons)
rospy.init_node('mock_tracked_persons')
rate = rospy.Rate(10)
# create speeds
speeds = np.random.normal(1.34, 0.26, size=50)
while not rospy.is_shutdown():
index = 0
counter = 0
tracked_persons = TrackedPersons()
tracked_persons.header.seq = counter
tracked_persons.header.frame_id = "odom"
tracked_persons.header.stamp = rospy.Time.now()
# (createTrackedPerson( trackId, x, y, theta, speed ) )
tracked_persons.tracks.append(
createTrackedPerson(01, 5, 4, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(02, 6, 5.45878, 270, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(03, 1.3 + 7.22, 5.70, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(04, 7.22, 7.33, 290, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(05, 2 + 8.92, 8.42, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(06, 2 + 7.92, 10.41, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(07, 2 + 7.2, 9.44, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(8, 2 + 7, 14 - 2, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(9, 2 + 5.5, 14.4123 - 2, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(10, 5 - 1, 18.595 - 5, 280, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(11, 5 - 1, 20 - 5, 270, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(12, 6 - 1, 21.5491 - 5, 240, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(13, 7.48044 - 1, 19 - 5.7, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(14, 6, 24.5463, 45, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(15, 8, 28, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(16, 10.4458, 23, 68, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(17, 11.5004, 27, 88, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(18, 14, 25.4389, 20, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(19, 15, 21, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(20, 15, 22.4308, 92, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(21, 15.4676, 24, 91, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(22, 16.5423, 25.4178, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(23, 18, 20, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(24, 18.5532, 21.5011, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(25, 15.4739, 16.5314, 45, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(26, 20, 25.5746, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(27, 21.5327, 24, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(28, 22, 26.4632, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(29, 21, 18, 45, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(30, 23, 20.4335, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(31, 23.4972, 21.4055, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(32, 23.4025, 22.4749, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(33, 24.5281, 18.5868, 54, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(34, 16.554, 3.40568 - 2, 94, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(35, 14.8, 6 - 3, 94, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(36, 20, 4, 0, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(37, 19, 12, 25, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(38, 23, 8, 50, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(39, 24, 10, 90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(40, 25, 12, 120, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(41, 7.51, 22.41, 80, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(42, 8.21, 25.7, 81, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(43, 3.31, 27.7, 81, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(44, 11.421, 18.7, 75, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(45, 25.21, 27.0, 85, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(46, 18.23, 6.87, -91, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(47, 18.6, 8.90, -90, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(48, 20.4, 7.87, 85, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(49, 15.684, 10.74, 75, speeds[index]))
tracked_persons.tracks.append(
createTrackedPerson(50, 15.72, 13.51, 70, speeds[index]))
trackPublisher.publish(tracked_persons)
counter += 1
index += 1
rate.sleep()
currentCycle = 0
currentAngle = 0.0
angleStep = 4.5 * pi / 180.
idShift = 0
updateRateHz = 10
# Test coordinate frame for checking if mapping into the fixed frame works correctly
frameOffset = (0, 0, 0)
frameOrientation = tf.transformations.quaternion_from_euler(0, 0, 0) # 90.0 / 180.0 * pi
print("Sending test messages on " + observationTopic + " and " + trackTopic)
rate = rospy.Rate(updateRateHz)
while not rospy.is_shutdown():
br.sendTransform(frameOffset, frameOrientation, rospy.Time.now(), "test_tf_frame", "odom")
trackedPersons = TrackedPersons()
trackedPersons.header.frame_id = "/test_tf_frame"
trackedPersons.header.stamp = rospy.Time.now()
detectedPersons = DetectedPersons()
detectedPersons.header = trackedPersons.header
tracks = trackedPersons.tracks;
detections = detectedPersons.detections;
createTrackAndDetection(tracks, detections, idShift+0, 3, currentAngle, 2.0)
createTrackAndDetection(tracks, detections, idShift+1, 7, currentAngle + pi / 2, 2.5)
createTrackAndDetection(tracks, detections, idShift+2, -1, currentAngle + pi / 1, 3.0)
createTrackAndDetection(tracks, detections, idShift+3, -1, currentAngle + pi * 1.5, cos(currentAngle) * 3.5 + 7.0)
createTrackAndDetection(tracks, detections, idShift+4, 88, 0.0, 0.0)
def createTrackedPersons(self, timestamp):
trackedPersons = TrackedPersons()
trackedPersons.header.stamp = timestamp
trackedPersons.header.frame_id = self.trackingFrame
for trackKey, track in self.database.getTracks().iteritems():
waypoints = self.database.getWaypoints(track)
if waypoints:
firstWaypoint = waypoints[0]
lastWaypoint = waypoints[-1]
# Check if we are before the first or past the last waypoint
beforeFirstWaypoint = timestamp.to_sec(
) < firstWaypoint["timestamp"]
behindLastWaypoint = timestamp.to_sec(
) > lastWaypoint["timestamp"]
if not beforeFirstWaypoint and not behindLastWaypoint:
trackedPerson = TrackedPerson()
trackedPerson.track_id = self.database.getTrackId(trackKey)
trackedPerson.is_occluded = False
trackedPerson.age = rospy.Time(firstWaypoint["timestamp"])
# Find adjacent waypoints for linear interpolation of tracked person's position
previousWaypoint = nextWaypoint = None
for waypoint in waypoints:
previousWaypoint = nextWaypoint
nextWaypoint = waypoint
if nextWaypoint["timestamp"] > timestamp.to_sec():
break
try:
# If there is only one waypoint for this track, previousWaypoint will be None
nextPosition = self.transformer.toCommonFrame(
nextWaypoint, self.trackingFrame)
nextTimestamp = nextWaypoint["timestamp"]
# Determine waypoint segment duration and distance
if previousWaypoint is not None:
previousPosition = self.transformer.toCommonFrame(
previousWaypoint, self.trackingFrame)
previousTimestamp = previousWaypoint["timestamp"]
segmentDuration = nextTimestamp - previousTimestamp
alpha = (timestamp.to_sec() -
previousTimestamp) / segmentDuration
diffVector = nextPosition - previousPosition
else:
previousPosition = nextPosition
segmentDuration = 1.0
alpha = 0.0
diffVector = numpy.array([0, 0])
except tf.Exception:
continue
# Linear interpolation
interpolatedPosition = previousPosition + diffVector * alpha
velocity = diffVector / segmentDuration
trackedPerson.pose.pose.position.x, trackedPerson.pose.pose.position.y = interpolatedPosition
trackedPerson.pose.covariance[
2 * 6 + 2] = trackedPerson.pose.covariance[
3 * 6 +
3] = trackedPerson.pose.covariance[4 * 6 +
4] = 99999999
yaw = math.atan2(velocity[1], velocity[0])
quaternion = tf.transformations.quaternion_from_euler(
0, 0, yaw)
trackedPerson.pose.pose.orientation = Quaternion(
x=quaternion[0],
y=quaternion[1],
z=quaternion[2],
w=quaternion[3])
trackedPerson.twist.twist.linear.x, trackedPerson.twist.twist.linear.y = velocity
trackedPersons.tracks.append(trackedPerson)
return trackedPersons
def publish_obstacles(self):
with self.lock:
if self.transport_data is None:
return
# non-leg obstacles
timestamp, xx, yy, clusters, is_legs, cogs, radii, tf_rob_in_fix = self.transport_data
# tracks
track_ids = []
tracks_latest_pos, tracks_color = [], []
tracks_in_frame, tracks_velocities = [], []
tracks_radii = []
for trackid in self.tracker.active_tracks:
track = self.tracker.active_tracks[trackid]
xy = np.array(track.pos_history[-1])
is_track_in_frame = True
if trackid in self.tracker.latest_matches:
color = (0.,1.,0.,1.) # green
elif trackid in self.tracker.new_tracks:
color = (0.,0.,1.,1.) # blue
else:
color = (0.7, 0.7, 0.7, 1.)
is_track_in_frame = False
track_ids.append(trackid)
tracks_latest_pos.append(xy)
tracks_color.append(color)
tracks_in_frame.append(is_track_in_frame)
tracks_velocities.append(track.estimate_velocity())
tracks_radii.append(track.avg_radius())
# publish trackedpersons
from spencer_tracking_msgs.msg import TrackedPersons, TrackedPerson
pub = rospy.Publisher("/tracked_persons", TrackedPersons, queue_size=1)
tp_msg = TrackedPersons()
tp_msg.header.frame_id = self.kFixedFrame
tp_msg.header.stamp = timestamp
for trackid, xy, in_frame, vel, radius in zip(track_ids, tracks_latest_pos, tracks_in_frame, tracks_velocities, tracks_radii):
# if not in_frame:
# continue
tp = TrackedPerson()
tp.track_id = trackid
tp.is_occluded = False
tp.is_matched = in_frame
tp.detection_id = trackid
tp.pose.pose.position.x = xy[0]
tp.pose.pose.position.y = xy[1]
heading_angle = np.arctan2(vel[1], vel[0]) # guess heading from velocity
from geometry_msgs.msg import Quaternion
tp.pose.pose.orientation = Quaternion(
*tf.transformations.quaternion_from_euler(0, 0, heading_angle))
tp.twist.twist.linear.x = vel[0]
tp.twist.twist.linear.y = vel[1]
tp.twist.twist.angular.z = 0 # unknown
tp_msg.tracks.append(tp)
pub.publish(tp_msg)
pub = rospy.Publisher('/obstacles', ObstacleArrayMsg, queue_size=1)
obstacles_msg = ObstacleArrayMsg()
obstacles_msg.header.stamp = timestamp
obstacles_msg.header.frame_id = self.kFixedFrame
for trackid, xy, in_frame, vel, radius in zip(track_ids, tracks_latest_pos, tracks_in_frame, tracks_velocities, tracks_radii):
if not in_frame:
continue
# Add point obstacle
obst = ObstacleMsg()
obst.id = trackid
obst.polygon.points = [Point32()]
obst.polygon.points[0].x = xy[0]
obst.polygon.points[0].y = xy[1]
obst.polygon.points[0].z = 0
obst.radius = radius
yaw = np.arctan2(vel[1], vel[0])
q = tf.transformations.quaternion_from_euler(0,0,yaw)
obst.orientation = Quaternion(*q)
obst.velocities.twist.linear.x = vel[0]
obst.velocities.twist.linear.y = vel[1]
obst.velocities.twist.linear.z = 0
obst.velocities.twist.angular.x = 0
obst.velocities.twist.angular.y = 0
obst.velocities.twist.angular.z = 0
obstacles_msg.obstacles.append(obst)
pub.publish(obstacles_msg)
pub = rospy.Publisher('/close_nonleg_obstacles', ObstacleArrayMsg, queue_size=1)
MAX_DIST_STATIC_CLUSTERS_M = 3.
cogs_in_fix = []
for i in range(len(cogs)):
cogs_in_fix.append(apply_tf(cogs[i], Pose2D(tf_rob_in_fix)))
obstacles_msg = ObstacleArrayMsg()
obstacles_msg.header.stamp = timestamp
obstacles_msg.header.frame_id = self.kFixedFrame
for c, cog_in_fix, cog_in_rob, r, is_leg in zip(clusters, cogs_in_fix, cogs, radii, is_legs):
if np.linalg.norm(cog_in_rob) < self.kRobotRadius:
continue
if len(c) < self.kMinClusterSize:
continue
# leg obstacles are already published in the tracked obstacles topic
if is_leg:
continue
# close obstacles only
if np.linalg.norm(cog_in_rob) > MAX_DIST_STATIC_CLUSTERS_M:
continue
# Add point obstacle
obst = ObstacleMsg()
obst.id = 0
obst.polygon.points = [Point32()]
obst.polygon.points[0].x = cog_in_fix[0]
obst.polygon.points[0].y = cog_in_fix[1]
obst.polygon.points[0].z = 0
obst.radius = r
yaw = 0
q = tf.transformations.quaternion_from_euler(0,0,yaw)
from geometry_msgs.msg import Quaternion
obst.orientation = Quaternion(*q)
obst.velocities.twist.linear.x = 0
obst.velocities.twist.linear.y = 0
obst.velocities.twist.linear.z = 0
obst.velocities.twist.angular.x = 0
obst.velocities.twist.angular.y = 0
obst.velocities.twist.angular.z = 0
obstacles_msg.obstacles.append(obst)
pub.publish(obstacles_msg)
pub = rospy.Publisher('/obstacle_markers', MarkerArray, queue_size=1)
# delete all markers
ma = MarkerArray()
mk = Marker()
mk.header.frame_id = self.kFixedFrame
mk.ns = "obstacles"
mk.id = 0
mk.type = 0 # ARROW
mk.action = 3 # deleteall
ma.markers.append(mk)
pub.publish(ma)
# publish tracks
ma = MarkerArray()
id_ = 0
# track endpoint
for trackid, xy, in_frame, vel in zip(track_ids, tracks_latest_pos, tracks_in_frame, tracks_velocities):
if not in_frame:
continue
normvel = np.linalg.norm(vel)
if normvel == 0:
continue
mk = Marker()
mk.header.frame_id = self.kFixedFrame
mk.ns = "tracks"
mk.id = trackid
mk.type = 0 # ARROW
mk.action = 0
mk.scale.x = np.linalg.norm(vel)
mk.scale.y = 0.1
mk.scale.z = 0.1
mk.color.r = color[0]
mk.color.g = color[1]
mk.color.b = color[2]
mk.color.a = color[3]
mk.frame_locked = True
mk.pose.position.x = xy[0]
mk.pose.position.y = xy[1]
mk.pose.position.z = 0.03
yaw = np.arctan2(vel[1], vel[0])
q = tf.transformations.quaternion_from_euler(0,0,yaw)
mk.pose.orientation = Quaternion(*q)
ma.markers.append(mk)
pub.publish(ma)
