def publish(self, publisher, real = False):
costGrid = OccupancyGrid()
costGrid.header.frame_id = self.frame_id
costGrid.header.stamp = rospy.Time.now()
costGrid.info = self.map_info
temparr = copy.deepcopy(self.data) #protect ourselves from volitility
if not real:
# map cost_map to between 0 and 127 for fancy colors in rviz
maxVal = max(temparr)
minVal = float('inf')
for cost in temparr:
if not (cost == 0) and (cost < minVal): minVal = cost
minVal *= 1.01
factor = 90.0/(maxVal - minVal)
if(maxVal == minVal): return
# costGrid.data = [(int((i - minVal) * factor) if (i != 0) else 0) for i in cost_map.data]
costGrid.data = []
for i in temparr:
if(i!=0):
costGrid.data.append(int((i - minVal) * factor))
else:
costGrid.data.append(0)
else: costGrid.data = temparr
publisher.publish(costGrid)
def setUp(self):
og = OccupancyGrid()
og.info.resolution = 0.5
og.info.height = 20
og.info.width = 20
og.info.origin.position.x = 0.0
og.info.origin.position.y = 0.0
og.info.origin.position.y = 0.0
og.info.origin.orientation.z = 0.0
og.info.origin.orientation.w = 0.0
og.info.origin.orientation.x = 0.0
og.info.origin.orientation.y = 0.0
mapArray = np.array([0] * 400)
mapArray.shape = (20, 20)
for xi in range(20):
for yi in range(20):
if xi < 3 or xi > 15:
mapArray[xi, yi] = 100
if yi < 3 or yi > 15:
mapArray[xi, yi] = 100
if yi < 10 and xi > 10:
mapArray[xi, yi] = 75
mapArray.shape = 400
og.data = list(mapArray)
self.mapData = MapData(og)
def map_message(self):
""" Return a nav_msgs/OccupancyGrid representation of this map. """
grid_msg = OccupancyGrid()
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
grid_msg.info.resolution = self.occ_map.map_res
grid_msg.info.width = self.occ_map.width
grid_msg.info.height = self.occ_map.height
grid_msg.info.origin = Pose(Point(self.occ_map.map_limit[0], self.occ_map.map_limit[2], 0),
Quaternion(0, 0, 0, 1))
flat_grid = copy.deepcopy(self.map.reshape((self.occ_map.map_size,)))
for i in range(self.occ_map.map_size):
if flat_grid[i] > self.occ_map.prob_occ:
flat_grid[i] = 100
elif flat_grid[i] < self.occ_map.prob_free:
flat_grid[i] = 0
else:
flat_grid[i] = -1
flat_grid = np.round(flat_grid)
flat_grid = flat_grid.astype(int)
grid_msg.data = list(flat_grid)
return grid_msg
def atlaas_grid(filepath, var_threshold=0.1, stamp=None, frame_id="/map"):
""" Usage:
atlaas.merge("atlaas.*x*.tif", "out.tif")
if os.path.isfile("out.tif"):
atlaas_grid("out.tif")
"""
g = gdal2(filepath)
bnp = g.bands[g.names["N_POINTS"]]
bma = g.bands[g.names["Z_MAX"]]
bme = g.bands[g.names["Z_MEAN"]]
bva = g.bands[g.names["VARIANCE"]]
data = numpy.where(bva > var_threshold, bma, bme)
delta = data.max() - data.min()
ddis = (100.0 * (data - data.min()) / delta).astype("uint8")
ddis[bnp < 1] = 0 # no points, unknown
og = OccupancyGrid()
og.data = ddis.flatten()
if stamp:
og.header.stamp = stamp
og.header.frame_id = frame_id
og.info.resolution = g.scale_x
og.info.height, og.info.width = data.shape
og.info.origin.position.x, og.info.origin.position.y = g.u2c(g.utm_x, g.utm_y)
og.info.origin.orientation.x = 1 # flip to transform UTM-ROS (scale_y < 0)
return og
def load_map(fp):
ogrid = OccupancyGrid()
step = None
offset = None
yaml_file = fp + ".yaml"
csv_file = fp + ".csv"
with open(yaml_file, "r") as infile:
for k, v in yaml.load(infile.read()).iteritems():
if k == "Header":
ogrid.header = v
elif k == "MapMetaData":
ogrid.info = v
step = v.resolution
offset = (v.origin.position.x, v.origin.position.y)
elif k == "GridFile":
print "GridFile: ", v
else:
print "Unexpected k : ", k
raise TypeError("Unexpected key type in yaml file: " + yaml_file)
ogrid.data = list(np.loadtxt(csv_file, dtype=np.int8, delimiter=","))
print "Map loaded"
return ogrid, step, offset
def setUp(self):
self.bg = BumpGuesser("bump_filter", 1000, (10, 10), 0.8)
og = OccupancyGrid()
og.info.resolution = 0.5
og.info.height = 20
og.info.width = 20
og.info.origin.position.x = 0.0
og.info.origin.position.y = 0.0
og.info.origin.orientation.z = 0.0 # 5 * 2.0**0.5
og.info.origin.orientation.w = 0.0 # 5 * 2.0**0.5
og.info.origin.orientation.x = 0.0
og.info.origin.orientation.y = 0.0
mapArray = np.array([0] * 400)
mapArray.shape = (20, 20)
for xi in range(20):
for yi in range(20):
if xi < 3 or xi > 15:
mapArray[xi, yi] = 100
if yi < 3 or yi > 15:
mapArray[xi, yi] = 100
if yi < 10 and xi > 10:
mapArray[xi, yi] = 75
mapArray.shape = 400
og.data = list(mapArray)
mapData = MapData(og)
self.bg.addMap(mapData)
def to_message(self):
""" Return a nav_msgs/OccupancyGrid representation of this map. """
grid_msg = OccupancyGrid()
# Set up the header.
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
# .info is a nav_msgs/MapMetaData message.
grid_msg.info.resolution = self.resolution
grid_msg.info.width = self.width
grid_msg.info.height = self.height
# Rotated maps are not supported... quaternion represents no
# rotation.
grid_msg.info.origin = Pose(Point(self.origin_x, self.origin_y, 0),
Quaternion(0, 0, 0, 1))
# Flatten the numpy array into a list of integers from 0-100.
# This assumes that the grid entries are probalities in the
# range 0-1. This code will need to be modified if the grid
# entries are given a different interpretation (like
# log-odds).
flat_grid = self.grid.reshape((self.grid.size,)) * 100
grid_msg.data = list(np.round(flat_grid))
return grid_msg
def viz_data(grid, closed):
# Visualize DATA
global pub
global grid_res, grid_transform
occ_msg = OccupancyGrid()
occ_msg.info.resolution = grid_res
occ_msg.info.width = len(grid.nodelist)
occ_msg.info.height = len(grid.nodelist[0])
occ_msg.header.frame_id = "map"
occ_msg.info.origin.position.x = grid_transform[0, 3]
occ_msg.info.origin.position.y = grid_transform[1, 3]
quaternion = tf.transformations.quaternion_from_matrix(grid_transform)
occ_msg.info.origin.orientation.x = quaternion[0]
occ_msg.info.origin.orientation.y = quaternion[1]
occ_msg.info.origin.orientation.z = quaternion[2]
occ_msg.info.origin.orientation.w = quaternion[3]
occ_data = [0] * (occ_msg.info.width * occ_msg.info.height)
width = occ_msg.info.width
height = occ_msg.info.height
# occ_data[width * start.x + start.y] = 100
# occ_data[width * goal.x + goal.y] = 100
top_cost = 1
for node in closed:
if node.g_cost > top_cost:
top_cost = node.g_cost
for node in closed:
cost = node.g_cost / top_cost
cost *= 225
if cost > 99:
cost -= 228
occ_data[width * node.x + node.y] = cost
occ_msg.data = occ_data
pub.publish(occ_msg)
def read_map(data):
global workingOnMap
workingOnMap = True
print "manually reducing map resolution"
# change the map's resolution
newOccGrid, newMapHeight, newMapWidth = increaseMapResolution(data)
# expand the obstacles
newOccGrid = expandObstacles(newOccGrid, desiredMapRes, newMapWidth, newMapHeight)
# publish the new grid
newPublishedGrid = OccupancyGrid()
newPublishedGrid.info.resolution = desiredMapRes
newPublishedGrid.info.origin.position.x= data.info.origin.position.x
newPublishedGrid.info.origin.position.y= data.info.origin.position.y
newPublishedGrid.info.width = newMapWidth
newPublishedGrid.info.height = newMapHeight
newPublishedGrid.data = tuple(newOccGrid)
print "publishing map"
scaledMapPub.publish(newPublishedGrid)
# publish the amount that the obstacles were expanded by
expansionVal = Float64()
expansionVal.data = expansionWidth
obstacleExpansionDimensionPub.publish(expansionVal)
workingOnMap = False
def updateCombined():
global data0
global data1
global data2
global mapData
global searchedCombinePub
rospy.wait_for_message('robot_0/robotSearched', OccupancyGrid, timeout=None)
rospy.wait_for_message('robot_1/robotSearched', OccupancyGrid, timeout=None)
rospy.wait_for_message('robot_2/robotSearched', OccupancyGrid, timeout=None)
mapMsg=OccupancyGrid()
while not rospy.is_shutdown():
map0 = numpy.array(data0.data)
map1 = numpy.array(data1.data)
map2 = numpy.array(data2.data)
combined = numpy.minimum(map0,map1)
combined = numpy.minimum(combined,map2)
mapMsg.header.stamp=rospy.Time.now()
mapMsg.header.frame_id=mapData.header.frame_id
mapMsg.info.resolution=mapData.info.resolution
mapMsg.info.width=mapData.info.width
mapMsg.info.height=mapData.info.height
mapMsg.info.origin=mapData.info.origin
mapMsg.data=combined.tolist()
searchedCombinePub.publish(mapMsg)
rospy.sleep(1.0)
def handleSearchedCombinedMessage(data): global findFrontierPub #get map dimensions data width=data.info.width height=data.info.height searchedMap = data.data frontier = [0] * (width * height) for h in range(height): for w in range(width): if searchedMap[h*width+w] == -1: frontier[h*width+w]=-1 if searchedMap[h*width+w] == 100: if isFrontier(searchedMap,h,w,height,width): frontier[h*width+w]=100 mapMsg=OccupancyGrid() mapMsg.header.stamp=rospy.Time.now() mapMsg.header.frame_id=data.header.frame_id mapMsg.info.resolution=data.info.resolution mapMsg.info.width=width mapMsg.info.height=height mapMsg.info.origin=data.info.origin mapMsg.data=frontier findFrontierPub.publish(mapMsg)
def updateCoverage(self):
# Reinitialize coverage map
ogm_shape = self.ogm.shape
self.coverage = numpy.zeros(ogm_shape)
# YOUR CODE HERE ------------------------------------------------------
# Update the coverage field using the self.robot_path veriable.
# We suppose that in every pose the robot covers an area of 2m x 2m
# around it
# 0 is for the uncovered, 100 is for the covered
# PS. Try to make it fast :)
# PS2. Do not have coverage values on obstacles or unknown space!
# If done correctly, the coverage will appear purple in rviz
# ---------------------------------------------------------------------
# Publishing coverage ogm to see it in rviz
coverage_ogm = OccupancyGrid()
coverage_ogm.header.frame_id = "map"
coverage_ogm.info = self.ogm_info
coverage_ogm.data = numpy.zeros(self.ogm_info.width * self.ogm_info.height)
for i in range(0, self.ogm_info.width):
for j in range(0, self.ogm_info.height):
coverage_ogm.data[i + self.ogm_info.width * j] = self.coverage[i][j]
self.coverage_publisher.publish(coverage_ogm)
def occ_grid_cb(data):
global p,ready,first
rospy.loginfo("map_reduction.py:occ_grid_cb() /ready_for_wps: %s",str(ready))
if not ready.data:
return
nav_map = OccupancyGrid()
w,h = data.info.width,data.info.height
pt = data.data
p = array(pt).reshape(w,h)#.T #<-- Transposes
if not 'grid_loc' in globals():
return
x,y = grid_loc.position.x, grid_loc.position.y
nav_map.info = data.info
if not 'size' in globals():
size = 64
if 'rtl' in globals() and rtl:
##Intelligently set mapsize, scale map, and send waypoints to home
pass
nav_map.info.width = size
nav_map.info.height = size
tmp_map = p[int(x)-size/2:int(x)+size/2,int(y)-size/2:int(y)+size/2]
if first:
tmp_map[:,:size/2] = 100
nav_map.data = tmp_map.flatten()
nav_map_pub.publish(nav_map)
def pubMap(self):
# Publish updated map
grid_msg = OccupancyGrid()
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
# .info is a nav_msgs/MapMetaData message.
grid_msg.info.resolution = self.resolution
grid_msg.info.width = self.map_info.width
grid_msg.info.height = self.map_info.height
# Rotated maps are not supported... quaternion represents no
# rotation.
grid_msg.info.origin = Pose(Point(self.map_origin[0], self.map_origin[1], 0),Quaternion(0, 0, 0, 1))
# Flatten the numpy array into a list of integers from 0-100.
# This assumes that the grid entries are probalities in the
# range 0-1. This code will need to be modified if the grid
# entries are given a different interpretation (like
# log-odds).
flat_grid = self.grid.reshape((self.grid_map.size,)) * 100
grid_msg.data = list(np.round(flat_grid))
self._map_data_pub.publish(grid_msg.info)
self._map_pub.publish(grid_msg)
return grid_msg
def run(self):
while self.is_looping():
navigation_tf_msg = TFMessage()
try:
motion_to_robot = almath.Pose2D(self.motion.getRobotPosition(True))
localization = self.navigation.getRobotPositionInMap()
exploration_path = self.navigation.getExplorationPath()
except Exception as e:
navigation_tf_msg.transforms.append(self.get_navigation_tf(almath.Pose2D()))
self.publishers["map_tf"].publish(navigation_tf_msg)
self.rate.sleep()
continue
if len(localization) > 0 and len(localization[0]) == 3:
navigation_to_robot = almath.Pose2D(localization[0][0], localization[0][1], localization[0][2])
navigation_to_motion = navigation_to_robot * almath.pinv(motion_to_robot)
navigation_tf_msg.transforms.append(self.get_navigation_tf(navigation_to_motion))
self.publishers["map_tf"].publish(navigation_tf_msg)
if len(localization) > 0:
if self.publishers["uncertainty"].get_num_connections() > 0:
uncertainty = Marker()
uncertainty.header.frame_id = "/base_footprint"
uncertainty.header.stamp = rospy.Time.now()
uncertainty.type = Marker.CYLINDER
uncertainty.scale = Vector3(localization[1][0], localization[1][1], 0.2)
uncertainty.pose.position = Point(0, 0, 0)
uncertainty.pose.orientation = self.get_ros_quaternion(
almath.Quaternion_fromAngleAndAxisRotation(0, 0, 0, 1))
uncertainty.color = ColorRGBA(1, 0.5, 0.5, 0.5)
self.publishers["uncertainty"].publish(uncertainty)
if self.publishers["map"].get_num_connections() > 0:
aggregated_map = None
try:
aggregated_map = self.navigation.getMetricalMap()
except Exception as e:
print("error " + str(e))
if aggregated_map is not None:
map_marker = OccupancyGrid()
map_marker.header.stamp = rospy.Time.now()
map_marker.header.frame_id = "/map"
map_marker.info.resolution = aggregated_map[0]
map_marker.info.width = aggregated_map[1]
map_marker.info.height = aggregated_map[2]
map_marker.info.origin.orientation = self.get_ros_quaternion(
almath.Quaternion_fromAngleAndAxisRotation(-1.57, 0, 0, 1))
map_marker.info.origin.position.x = aggregated_map[3][0]
map_marker.info.origin.position.y = aggregated_map[3][1]
map_marker.data = aggregated_map[4]
self.publishers["map"].publish(map_marker)
if self.publishers["exploration_path"].get_num_connections() > 0:
path = Path()
path.header.stamp = rospy.Time.now()
path.header.frame_id = "/map"
for node in exploration_path:
current_node = PoseStamped()
current_node.pose.position.x = node[0]
current_node.pose.position.y = node[1]
path.poses.append(current_node)
self.publishers["exploration_path"].publish(path)
self.rate.sleep()
def ExpandMap(occupancyGrid): lowerResGrid = OccupancyGrid(occupancyGrid.header, occupancyGrid.info, []) oldWidth = occupancyGrid.info.width lowerResGrid.info.resolution = .1 lowerResGrid.info.width = int(math.floor(float(occupancyGrid.info.width)/2)) lowerResGrid.info.height = int(math.floor(float(occupancyGrid.info.height)/2)) width = lowerResGrid.info.width height = lowerResGrid.info.height lowerResGrid.data = [-1]*width*height for i in range (0, height): for j in range (0, width): if occupancyGrid.data[(j*2) + (oldWidth * i*2)] >= 1 or \ occupancyGrid.data[(j*2) + (oldWidth * ((i*2)+1))] >= 1 or \ occupancyGrid.data[(j*2)+1 + (oldWidth * i*2)] >= 1 or \ occupancyGrid.data[(j*2)+1 + (oldWidth * ((i*2)+1))] >= 1: lowerResGrid.data[j + (width * i)] = 100 elif occupancyGrid.data[(j*2) + (oldWidth * i*2)] == 0 and \ occupancyGrid.data[(j*2) + (oldWidth * ((i*2)+1))] == 0 and \ occupancyGrid.data[(j*2)+1 + (oldWidth * i*2)] == 0 and \ occupancyGrid.data[(j*2)+1 + (oldWidth * ((i*2)+1))] == 0: lowerResGrid.data[j + (width * i)] = 0 else: lowerResGrid.data[j + (width * i)] = -1 expandedGrid = OccupancyGrid(lowerResGrid.header, lowerResGrid.info, lowerResGrid.data) expandedData = list(lowerResGrid.data) print "expanding" for i in range (0, height): for j in range (0, width): if (lowerResGrid.data[j + (width * i)] >= 1): for k in range (j - 2, j + 3): for l in range (i - 2, i + 3): if (k > 0 and k < width and l > 0 and l < height): expandedData[k + (width * l)] = 100 expandedGrid.data = tuple(expandedData) print "expanded" return expandedGrid, lowerResGrid
def image2ism(imgConfidence, imgClass, header):
if useTfForExtrinsic:
headFrame = header.frame_id
headFrame = str.join(
'/',
[strPart for strPart in headFrame.split('/') if strPart is not ''
]) # Complicated wat to remove the first '/' if it exists.
trans = tfBuffer.lookup_transform(targetFrameId, headFrame,
rospy.Time())
ipm.update_extrinsic_from_tf_transform(trans)
if ipm.isExtrinsicUpdated == False:
ipm.update_extrinsic(cam_roll, cam_pitch, cam_yaw, pCamera)
for objectType in pubOutputTopics.keys():
classNumber = outputTopicsNumber[objectType]
bwClass = imgClass == classNumber
imgConfidenceClass = np.zeros_like(imgConfidence)
imgConfidenceClass[bwClass] = imgConfidence[bwClass]
resample_input
if resample_input == 1.0:
cv_image = imgConfidenceClass
else:
cv_image = cv2.resize(imgConfidenceClass,
None,
fx=resample_input,
fy=resample_input,
interpolation=cv2.INTER_NEAREST)
imDimIn = cv_image.shape[0:2]
if ipm.isHomographyUpdated == False:
pRayStarts, pDst, rHorizon, rHorizonTrue, pSrc, pDstOut = ipm.update_homography(
imDimIn)
# A grid is only published when the homography is updated.
if ipm.isHomographyUpdated == True:
grid = ipm.makePerspectiveMapping(cv_image, match2Grid=match2Grid)
grid_msg = OccupancyGrid()
grid_msg.header = header
#grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = targetFrameId
grid_msg.info.resolution = grid_resolution
grid_msg.info.width = grid.shape[1]
grid_msg.info.height = grid.shape[0]
origin_x = ipm.distToMapping
origin_y = -float(grid.shape[0]) * grid_resolution / 2
origin_z = 0.0
grid_msg.info.origin = Pose(Point(origin_x, origin_y, origin_z),
Quaternion(0, 0, 0, 1))
grid_msg.data = np.flipud(grid).flatten()
pubOutputTopics[objectType].publish(grid_msg)
def publishCombined(self):
#Enter Main Loop
while not rospy.is_shutdown():
#Convert to Numpy Arrays
map = []
for i in range(0, self.numRobots):
map.append(numpy.array(self.searchedData[i].data))
combined2 = map[0]
if self.numRobots > 1:
#Find Minimum of all maps
for i in range(1, self.numRobots):
combined2 = numpy.minimum(combined2, map[i])
#Pack Occupancy Grid Message
mapMsg = OccupancyGrid()
mapMsg.header.stamp = rospy.Time.now()
mapMsg.header.frame_id = self.mapData.header.frame_id
mapMsg.info.resolution = self.mapData.info.resolution
mapMsg.info.width = self.mapData.info.width
mapMsg.info.height = self.mapData.info.height
mapMsg.info.origin = self.mapData.info.origin
mapMsg.data = combined2.tolist()
#Convert combined Occupancy grid values to grayscal image values
combined2[combined2 == -1] = 150 #Unknown -1->150 (gray)
combined2[combined2 == 100] = 255 #Not_Searched 100->255 (white)
#Searched=0 (black)
#Calculate percentage of open area searched
numNotSearched = combined2[combined2 == 255].size
numSearched = combined2[combined2 == 0].size
percentSearched = 100 * float(numSearched) / (numNotSearched +
numSearched)
percentSearchedMsg = Float32()
percentSearchedMsg.data = percentSearched
self.percentPub.publish(percentSearchedMsg)
#Pack Image Message
imageMsg = Image()
imageMsg.header.stamp = rospy.Time.now()
imageMsg.header.frame_id = self.mapData.header.frame_id
imageMsg.height = self.mapData.info.height
imageMsg.width = self.mapData.info.width
imageMsg.encoding = 'mono8'
imageMsg.is_bigendian = 0
imageMsg.step = self.mapData.info.width
imageMsg.data = combined2.tolist()
#Publish Combined Occupancy Grid and Image
self.searchedCombinePub.publish(mapMsg)
self.imagePub.publish(imageMsg)
#Update Every 0.5 seconds
rospy.sleep(1.0)
def pub_grid(self, *args):
grid = self.grid_drawer.img
ogrid = OccupancyGrid()
ogrid.header.frame_id = '/enu'
ogrid.header.stamp = rospy.Time.now()
ogrid.info = self.map_meta_data
ogrid.data = np.subtract(np.flipud(grid).flatten(), 1).astype(np.int8).tolist()
self.ogrid_pub.publish(ogrid)
def get_message(self):
ogrid = OccupancyGrid()
ogrid.header = mil_tools.make_header(frame="enu")
ogrid.info.resolution = self.resolution
ogrid.info.height, ogrid.info.width = self.grid.shape
ogrid.info.origin = self.origin
grid = np.copy(self.grid)
ogrid.data = np.clip(grid.flatten(), -100, 100).astype(np.int8)
return ogrid
def publishMap(worldmap, topicName, publisher, x, y, rot):
msg = OccupancyGrid()
msg.header.stamp = rospy.Time.now()
msg.header.frame_id = topicName
msg.info.resolution = 0.05
msg.info.width = worldmap.shape[0]
msg.info.height = worldmap.shape[1]
msg.info.origin.orientation = Quaternion(0, 0, 0, 1)
msg.info.origin.position.x = -x * msg.info.resolution
msg.info.origin.position.y = -y * msg.info.resolution
msg.data = 100 / (1 + np.exp(-worldmap))
msg.data[worldmap == 0] = -1
msg.data = msg.data.T.astype(np.int8).ravel()
publisher.publish(msg)
br = tf.TransformBroadcaster()
br.sendTransform(
(0, 0, 0),
tf.transformations.quaternion_from_euler(0, 0, -rot - np.pi / 2),
rospy.Time.now(), topicName, "base_link")
def get_message(self):
ogrid = OccupancyGrid()
ogrid.header = navigator_tools.make_header(frame="enu")
ogrid.info.resolution = self.resolution
ogrid.info.height, ogrid.info.width = self.grid.shape
ogrid.info.origin = self.origin
grid = np.copy(self.grid)
ogrid.data = np.clip(grid.flatten() - 1, -100, 100).astype(np.int8)
return ogrid
def get_exploration_occupancy_grid(self):
msg = OccupancyGrid()
msg.header = make_header("/map")
msg.info = self.map_info
buff = self.exploration_buffer.astype(np.int8)
buff[buff == 0] = 100
buff[buff == 1] = 50
msg.data = buff.reshape(self.map_info.height *
self.map_info.width).tolist()
return msg
def publish_change_grid(self): change_grid = OccupancyGrid() change_grid.header.stamp = rospy.Time.now() change_grid.header.frame_id = "map" change_grid.info.resolution = self.height/self.division change_grid.info.width = self.division change_grid.info.height = self.division change_grid.info.origin.orientation.w = 1 change_grid.data = [(self.change_detected[x][y])*25 for y in range(self.division) for x in range(self.division)] self.pub_change_grid.publish(change_grid)
def pub_grid(self, *args):
grid = self.grid_drawer.img
ogrid = OccupancyGrid()
ogrid.header.frame_id = '/world'
ogrid.info = self.map_meta_data
ogrid.data = np.subtract(np.flipud(grid).flatten(),
1).astype(np.int8).tolist()
self.ogrid_pub.publish(ogrid)
def mapMask(map1):
map2 = OccupancyGrid()
map2.header = map1.header
map2.info = map1.info
global offs
offs = map1.info.width
map2.info.origin.position.x = 0
map2.info.origin.position.y = 0
map2.data = [0 if x == -1 else x for x in map1.data]
pubM.publish(map2)
def publish_visibility_grid(self): visible_grid = OccupancyGrid() visible_grid.header.stamp = rospy.Time.now() visible_grid.header.frame_id = "map" visible_grid.info.resolution = self.height/self.division visible_grid.info.width = self.division visible_grid.info.height = self.division visible_grid.info.origin.orientation.w = 1 visible_grid.data = [self.convert(self.is_grid_active[x][y]) for y in range(self.division) for x in range(self.division)] self.pub_visibility_grid.publish(visible_grid)
def pub_ogrid(self, *args):
ogrid = OccupancyGrid()
ogrid.header = navigator_tools.make_header(frame="enu")
ogrid.info = self.map_metadata
# Over saturate and clip to get range of [-1, 1]
self.grid = np.clip(self.grid * 1000, -1, 1)
ogrid.data = self.grid.flatten().astype(np.int8).tolist()
self.ogrid_pub.publish(ogrid)
def mappublisher(m,height, width, resolution,morigin):
msg = OccupancyGrid()
msg.header.frame_id='map'
msg.info.resolution = resolution
msg.info.width = math.ceil(width/resolution)
msg.info.height = math.ceil(height/resolution)
msg.info.origin.position.x=-morigin[0]
msg.info.origin.position.y=-morigin[1]
msg.data=m
mappub.publish(msg)
def publish_map(self):
g = OccupancyGrid()
g.header.frame_id = "/cartographer_map"
g.info.resolution = self.resolution
g.info.width = self.width
g.info.height = self.height
g.info.origin = self.true_origin
g.info.map_load_time = rospy.Time.now()
g.data = self.MAP
self.map_pub.publish(g)
def publishCombined(self): #Enter Main Loop while not rospy.is_shutdown(): #Convert to Numpy Arrays map = [] for i in range(0, self.numRobots): map.append(numpy.array(self.searchedData[i].data)) combined2 = map[0] if self.numRobots > 1: #Find Minimum of all maps for i in range(1, self.numRobots): combined2 = numpy.minimum(combined2,map[i]) #Pack Occupancy Grid Message mapMsg=OccupancyGrid() mapMsg.header.stamp=rospy.Time.now() mapMsg.header.frame_id=self.mapData.header.frame_id mapMsg.info.resolution=self.mapData.info.resolution mapMsg.info.width=self.mapData.info.width mapMsg.info.height=self.mapData.info.height mapMsg.info.origin=self.mapData.info.origin mapMsg.data=combined2.tolist() #Convert combined Occupancy grid values to grayscal image values combined2[combined2 == -1] = 150 #Unknown -1->150 (gray) combined2[combined2 == 100] = 255 #Not_Searched 100->255 (white) #Searched=0 (black) #Calculate percentage of open area searched numNotSearched = combined2[combined2==255].size numSearched = combined2[combined2==0].size percentSearched = 100*float(numSearched)/(numNotSearched+numSearched) percentSearchedMsg = Float32() percentSearchedMsg.data = percentSearched self.percentPub.publish(percentSearchedMsg) #Pack Image Message imageMsg=Image() imageMsg.header.stamp = rospy.Time.now() imageMsg.header.frame_id = self.mapData.header.frame_id imageMsg.height = self.mapData.info.height imageMsg.width = self.mapData.info.width imageMsg.encoding = 'mono8' imageMsg.is_bigendian = 0 imageMsg.step = self.mapData.info.width imageMsg.data = combined2.tolist() #Publish Combined Occupancy Grid and Image self.searchedCombinePub.publish(mapMsg) self.imagePub.publish(imageMsg) #Update Every 0.5 seconds rospy.sleep(1.0)
def callback(data):
# tempolary hardcode the parameter
x_lim = -10
y_lim = -10
x_width = 20
y_width = 20
resol = 0.1
map_meta = data.info
N = int(x_width / resol) + 1
temp = np.ones((N, N)) * 50
dimh = MultiArrayDimension()
dimw = dimh
dimh.size = data.info.height
dimh.label = 'height'
dimh.stride = 48
dimw.size = data.info.width
dimw.label = 'width'
dimw.stride = 64
datanp = np.array(data.data, dtype=float)
datanp = datanp
datanp[datanp < 0] = 50
for i in range(data.info.height):
for j in range(data.info.width):
idx_x = round(
N / 2 -
map_meta.height / 2) #-data.info.origin.position.x/0.1)
idx_y = round(N / 2 - -data.info.origin.position.x / 0.1)
# temp[int(idx_x + i),int(idx_y + j)] = datanp[(i-1)*data.info.width+j]
for i in range(80):
for j in range(60):
temp[int(N / 2 - 40 + i), int(N / 2 - 30 + j)] = 0.1
map = OccupancyGrid()
map.data = temp.flatten()
map.info.width = int(N)
map.info.height = int(N)
map.info.resolution = 0.1
map.info.origin = map_meta.origin
# data.data
pub = rospy.Publisher('/TheMap', Float64MultiArray, queue_size=10)
pub_map = rospy.Publisher('/map_fixed', OccupancyGrid, queue_size=10)
a = Float64MultiArray()
a.layout.dim.append(dimh)
a.layout.dim.append(dimw)
a.layout.data_offset = 0
a.data = temp.flatten() / 100.
pub_map.publish(map)
pub.publish(a)
br = tf.TransformBroadcaster()
br.sendTransform((-map_meta.origin.position.x - 10,
-map_meta.origin.position.y - 10, 0.0),
(0.0, 0.0, 0.0, 1.0), rospy.Time.now(), "map", "world")
def publish_map(self):
(h, w) = self.explore_map.shape
map_msg = OccupancyGrid()
map_msg.info.resolution = UNIT
map_msg.info.width = w
map_msg.info.height = h
map_msg.info.origin.position.x = -self.x0
map_msg.info.origin.position.y = -self.y0
map_msg.data = (1 + 97 * self.explore_map.reshape(
(h * w, ))).astype(np.int8)
self.pub_map.publish(map_msg)
def publish_grid_map():
grid_map = OccupancyGrid()
grid_map.info.map_load_time = rospy.Time.now()
grid_map.info.width = slam_map.size
grid_map.info.height = slam_map.size
grid_map.info.resolution = slam_map.scale
grid_map.info.origin.position.x = -slam_map.size / 2 * slam_map.scale
grid_map.info.origin.position.y = -slam_map.size / 2 * slam_map.scale
grid_map.info.origin.position.z = 0
grid_map.data = slam_map.to_ros_grid()
pub.publish(grid_map)
def numpyToOcc(grid, res): msg = OccupancyGrid() msg.header.frame_id = "map" msg.data = grid.ravel() msg.info = MapMetaData() msg.info.height = grid.shape[0] msg.info.width = grid.shape[1] msg.info.resolution = res msg.info.origin = Pose(Point(0, 0, 0), Quaternion(0,0,0,1)) return msg
def publish_crowd_risk_model(self, crowd_risk_model): risk_grid = OccupancyGrid() risk_grid.header.stamp = rospy.Time.now() risk_grid.header.frame_id = "map" risk_grid.info.resolution = self.height/self.division risk_grid.info.width = self.division risk_grid.info.height = self.division risk_grid.info.origin.orientation.w = 1 risk_list = [crowd_risk_model[x][y] for x in range(self.division) for y in range(self.division)] risk_grid.data = self.normalize(risk_list, 0, 100) self.pub_risk_grid.publish(risk_grid)
def numpyToOcc(grid, origMsg): msg = OccupancyGrid() msg.header.frame_id = "map" msg.data = grid.ravel() msg.info = MapMetaData() msg.info.height = grid.shape[0] msg.info.width = grid.shape[1] msg.info.resolution = 0.05 msg.info.origin = origMsg.info.origin return msg
def convert_to_occ_grid(self):
res = OccupancyGrid()
res.header.stamp = rospy.Time.now()
res.header.frame_id = "odom_combined"
res.info.resolution = 0.1
res.info.width = 1000
res.info.height = 1000
res.info.origin.position.x = -50
res.info.origin.position.y = -50
res.data = self.grid
return res
def numpyToOcc(self, grid):
msg = OccupancyGrid()
msg.header.frame_id = "base_link"
msg.data = grid.ravel()
msg.info = MapMetaData()
msg.info.height = self.h
msg.info.width = self.w
msg.info.resolution = self.res
msg.info.origin = Pose(Point(0, 0, 0), Quaternion(0, 0, 0, 1))
return msg
def publish_grid_map():
grid_map = OccupancyGrid()
grid_map.info.map_load_time = rospy.Time.now()
grid_map.info.width = slam_map.size
grid_map.info.height = slam_map.size
grid_map.info.resolution = slam_map.scale
grid_map.info.origin.position.x = -slam_map.size / 2 * slam_map.scale
grid_map.info.origin.position.y = -slam_map.size / 2 * slam_map.scale
grid_map.info.origin.position.z = 0
grid_map.data = slam_map.to_ros_grid()
pub.publish(grid_map)
def to_message(self):
""" Return a nav_msgs/OccupancyGrid representation of this map. """
grid_msg = OccupancyGrid()
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
grid_msg.info.resolution = self.resolution
grid_msg.info.width = self.width
grid_msg.info.height = self.height
grid_msg.info.origin = Pose(Point(self.origin_x, self.origin_y, 0), Quaternion(0, 0, 0, 1))
grid_msg.data = self._numpy_to_data()
return grid_msg
def updateMap(e_o_indexes, w_map):
newGrid = OccupancyGrid()
newGrid.info = w_map.info
tmp_data = list(w_map.data)
for index in e_o_indexes:
if index >= 0 and index < len(w_map.data):
tmp_data[index] = 100
newGrid.data = tuple(tmp_data)
return newGrid
def publishListAsOccupancyGrid(list, publisher):
# TODO: does this need to be a deep copy?
occupancyGrid = OccupancyGrid()
occupancyGrid.info.height = G_GridRows
occupancyGrid.info.width = G_GridCols
occupancyGrid.info.resolution = G_GridResolution
occupancyGrid.info.origin.position.x = G_GridOriginX
occupancyGrid.info.origin.position.y = G_GridOriginY
occupancyGrid.info.origin.orientation.w = 1
occupancyGrid.header.frame_id = "map"
occupancyGrid.data = tuple(list)
publisher.publish(occupancyGrid)
def to_message(self):
grid_msg = OccupancyGrid()
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
grid_msg.info.resolution = self.resolution
grid_msg.info.width = self.width
grid_msg.info.height = self.height
grid_msg.info.origin = Pose(Point(self.origin_x, self.origin_y, 0),Quaternion(0, 0, 0, 1))
flat_grid = self.grid.reshape((self.grid.size,)) * 100
grid_msg.data = list(np.round(flat_grid))
return grid_msg
def create_test_occupancy_grid():
my_test_occupancy_grid = OccupancyGrid()
# test map meta data
my_test_occupancy_grid.info.width = 3
my_test_occupancy_grid.info.height = 3
my_test_occupancy_grid.info.resolution = 1.0
# test map obstacles
my_test_occupancy_grid.data = [0, 100, 0, 0, 100, 0, 0, 0, 0]
plot_all_the_trajectories(my_test_occupancy_grid)
def restrict(res, data):
d = len(data)
d = int(round(sqrt(d)))
msg = OccupancyGrid()
msg.header.frame_id = "map"
msg.info.resolution = res
msg.info.width = d
msg.info.height = d
msg.info.origin.position.x = -12.825
msg.info.origin.position.y = -12.825
msg.data = data
restPub.publish(msg)
def create_test_occupancy_grid():
my_test_occupancy_grid = OccupancyGrid()
# test map meta data
my_test_occupancy_grid.info.width = 3
my_test_occupancy_grid.info.height = 3
my_test_occupancy_grid.info.resolution = 1.0
# test map obstacles
my_test_occupancy_grid.data = [0, 100, 0, 0, 100, 0, 0, 0, 0]
do_stuff_with_map(my_test_occupancy_grid)
def create_map(self): test_map = OccupancyGrid() #Default config test_map.info.resolution = .1 #m/cell test_map.info.width = 200 #cells test_map.info.height = 200 #cells test_map.data = [] #Initialize p0 = self.calculateLogOddsProbability(self._l0)*100 for i in xrange(0, test_map.info.width*test_map.info.height): test_map.data.append( p0 ) return test_map
def mapResize(newRes, mapInfo, mapData):
oldRes = mapInfo.resolution
oldw = mapInfo.width
oldh = mapInfo.height
oldMapInfo = copy.deepcopy(mapInfo)
nMapData = []
nMapDataD = {}
#change the size of the new map. The offsets of the new map are already copied from the old map.
mapInfo.resolution = newRes
mapInfo.width = int(round( (oldw*(oldRes/newRes)) ))
mapInfo.height = int(round( (oldh*(oldRes/newRes)) ))
#print "old map dimensions"
#print oldMapInfo.width
#print oldMapInfo.height
#print "new map dimensions w x h"
#print mapInfo.width
#print mapInfo.height
#populate the new map at the defined resolution with all cells at -1
#print "generating the new map"
for x in range(mapInfo.width * mapInfo.height):
nMapDataD[x] = 0
#print "summing new blocks"
for i in range(len(mapData)):
gp = gridToGlobal(indexToGrid(i, oldMapInfo), oldMapInfo)
nIndex = gridToIndex(globalToGrid(gp, mapInfo), mapInfo)
if nIndex >= (mapInfo.width * mapInfo.height -1):
nIndex = mapInfo.width * mapInfo.height-1
nMapDataD[nIndex] = (nMapDataD[nIndex] + mapData[i])
for i in nMapDataD:
value = nMapDataD[i] / ((newRes*newRes) - (oldRes * oldRes))
if value > 5:
value = 100
elif value < 0:
value = -1
else:
value = 0
nMapData.append(numpy.int8(value))
newMapOC = OccupancyGrid()
newMapOC.info = mapInfo
newMapOC.data = tuple(nMapData)
return newMapOC
def ConvertMap(self, map_msg):
#Convert an OccupancyGrid map message into the internal representation. This allocates a map_t and returns it.
map = OccupancyGrid()
map.data = list(copy.deepcopy(map_msg.data))
for i in range(map_msg.info.width * map_msg.info.height):
if map_msg.data[i] == 0:
map.data[i] = -1
elif map_msg.data[i] == 100:
map.data[i] = 1
else:
map.data[i] = 0
return map
def run(self):
"""
Starts ros loop
"""
while not rospy.is_shutdown():
if self.costmap is not None:
costmap_msgs = OccupancyGrid()
costmap_msgs.info = self.metadata
costmap_msgs.data = np.ravel(self.costmap).tolist()
self.pub.publish(costmap_msgs)
self.rate.sleep()
def grilla2occupancy_grid(self):
mapa_msg = OccupancyGrid()
mapa_msg.header.frame_id = 'mapa'
mapa_msg.info.resolution = self.resolucion
mapa_msg.info.width = self.dimension_x
mapa_msg.info.height = self.dimension_y
mapa_msg.data = range(self.dimension_x * self.dimension_y)
for i in range(len(self.grilla.flat)):
mapa_msg.data[i] = self.grilla.flat[i]
return mapa_msg
def genDummy(self):
g = OccupancyGrid()
g.info.resolution = 0.05
g.info.width = 256
g.info.height = 128
tiles = []
for x in range(0, 512):
for y in range(0, 512):
tiles.append(Int8(round(np.random.random(1)[0] * 0.51) * 100))
g.data = tiles
print("generated occupancy grid")
return g
def to_message(self):
""" Return a nav_msgs/OccupancyGrid representation of this map. """
grid_msg = OccupancyGrid()
grid_msg.header.stamp = rospy.Time.now()
grid_msg.header.frame_id = "map"
grid_msg.info.resolution = self.resolution
grid_msg.info.width = self.width
grid_msg.info.height = self.height
grid_msg.info.origin = Pose(Point(self.origin_x, self.origin_y, 0),
Quaternion(0, 0, 0, 1))
grid_msg.data = self._numpy_to_data()
return grid_msg
def atlaas8u_grid(filepath, stamp=None, frame_id="/map"):
g = gdal2(filepath)
b = g.bands[0] if len(g.bands.shape) > 2 else g.bands
og = OccupancyGrid()
og.data = (b.astype("float") / 2.55).astype("uint8").flatten()
if stamp:
og.header.stamp = stamp
og.header.frame_id = frame_id
og.info.resolution = g.scale_x
og.info.height, og.info.width = b.shape
og.info.origin.position.x, og.info.origin.position.y = g.u2c(g.utm_x, g.utm_y)
og.info.origin.orientation.x = 1 # flip to transform UTM-ROS (scale_y < 0)
return og
def make_ogrid(self, np_arr, size, center):
np_center = np.array(center)
np_origin = np.append((np_center - size / 2)[:2], 0)
origin = mil_tools.numpy_quat_pair_to_pose(np_origin, [0, 0, 0, 1])
ogrid = OccupancyGrid()
ogrid.header = mil_tools.make_header(frame='enu')
ogrid.info.origin = origin
ogrid.info.width = size / self.resolution
ogrid.info.height = size / self.resolution
ogrid.info.resolution = self.resolution
ogrid.data = np.clip(np_arr.flatten() - 1, -100, 100).astype(np.int8)
return ogrid
def update_map(grid, update):
xgrid = OccupancyGrid()
xgrid.header.stamp = update.header.stamp
xgrid.header.frame_id = update.header.frame_id
xgrid.info = grid.info
xgrid.data = grid.data[:]
i = 0
for yi in range(update.height):
for xi in range(update.width):
index = (update.y+yi)*xgrid.info.width + xi + update.x
xgrid.data[index] = update.data[i]
i+=1
return xgrid
def get_message(self):
if self.grid is None:
fprint("Ogrid was requested but no ogrid was found. Using blank.", msg_color='yellow')
self.grid = np.zeros((self.height / self.resolution, self.width / self.resolution))
ogrid = OccupancyGrid()
ogrid.header = navigator_tools.make_header(frame="enu")
ogrid.info.resolution = self.resolution
ogrid.info.height, ogrid.info.width = self.grid.shape
ogrid.info.origin = self.origin
grid = np.copy(self.grid)
ogrid.data = np.clip(grid.flatten() - 1, -100, 100).astype(np.int8)
return ogrid
def publish_grid(self):
'''
Take the occupancy grid and send it out over ros with timestamps and whatnot.
'''
t = rospy.Time.now()
header = Header(stamp=t, frame_id='/map')
# Populate occ grid msg
occ_msg = OccupancyGrid()
occ_msg.header = header
occ_msg.info = self.meta_data
# Make sure values don't go out of range
occ_grid = self.searched + self.markers - 1
occ_msg.data = np.clip(occ_grid.flatten(), -1, 100)
self.occ_grid_pub.publish(occ_msg)
