class MapGuesser(object):
def __init__(self, name, nPoints, nBins, announce=False):
self.name = name
self.nBins = nBins
self.nPoints = nPoints
self.announce = announce
self.mapData = MapData(np.array([[0.0,0.0]]), (0.0,0.0), (1.0,1.0))
self.guesser = Guesser(self.name, (0.0, 0.0, 2*math.pi),
"location",
(self.nBins[0],self.nBins[1],1))
def addMap(self, newMapData):
assert isinstance(newMapData, MapData)
self.mapData = newMapData
# Pack the map data into a list of Point objects, since that's
# what the perfesser wants for input. This will make the grid
# into a histogram with which to filter other input points.
self.mapPointList = []
for xi in range(self.mapData.mapArray.shape[0]):
for yi in range(self.mapData.mapArray.shape[1]):
if self.mapData.mapArray[xi,yi] < 0.5:
p = Pt()
p.point = (self.mapData.orig[0] + xi * self.mapData.ints[0],
self.mapData.orig[1] + yi * self.mapData.ints[1],
0.0)
self.mapPointList.append(p)
def handle_guess(self, greq):
"""
Takes an input guess (a list of Point objects) and throws out
the points that seem impossible. Then resamples to return a list
of equally probable points. Most of this functionality is provided
via the perfesser's guesser methods.
"""
# Check input types
assert isinstance(greq, GuessRequest)
assert isinstance(greq.inPoints, list)
assert isinstance(greq.inPoints[0], Pt)
self.guesser.newPoints(self.mapPointList)
pts = Belief()
pts.points = greq.inPoints
self.guesser.update(pts)
# Return
gresp = GuessResponse(sender = self.name,
source_stamp = rospy.Time.now(),
source_data = "",
outPoints = self.guesser.outPoints(),
no_data = False)
return gresp
class MapGuesser(object):
def __init__(self, name, nPoints, nBins, announce=False):
self.name = name
self.nBins = nBins
self.nPoints = nPoints
self.announce = announce
self.mapData = MapData(np.array([[0.0, 0.0]]), (0.0, 0.0), (1.0, 1.0))
self.guesser = Guesser(self.name, (0.0, 0.0, 2 * math.pi), "location",
(self.nBins[0], self.nBins[1], 1))
def addMap(self, newMapData):
assert isinstance(newMapData, MapData)
self.mapData = newMapData
# Pack the map data into a list of Point objects, since that's
# what the perfesser wants for input. This will make the grid
# into a histogram with which to filter other input points.
self.mapPointList = []
for xi in range(self.mapData.mapArray.shape[0]):
for yi in range(self.mapData.mapArray.shape[1]):
if self.mapData.mapArray[xi, yi] < 0.5:
p = Pt()
p.point = (self.mapData.orig[0] +
xi * self.mapData.ints[0],
self.mapData.orig[1] +
yi * self.mapData.ints[1], 0.0)
self.mapPointList.append(p)
def handle_guess(self, greq):
"""
Takes an input guess (a list of Point objects) and throws out
the points that seem impossible. Then resamples to return a list
of equally probable points. Most of this functionality is provided
via the perfesser's guesser methods.
"""
# Check input types
assert isinstance(greq, GuessRequest)
assert isinstance(greq.inPoints, list)
assert isinstance(greq.inPoints[0], Pt)
self.guesser.newPoints(self.mapPointList)
pts = Belief()
pts.points = greq.inPoints
self.guesser.update(pts)
# Return
gresp = GuessResponse(sender=self.name,
source_stamp=rospy.Time.now(),
source_data="",
outPoints=self.guesser.outPoints(),
no_data=False)
return gresp
class BumpGuesser(object):
def __init__(self, name, nPoints, nBins, wallError, announce=False):
self.name = name
self.nBins = nBins
self.nPoints = nPoints
# wallError is the probability that a bump is from a feature that
# is on the map. You can bump into moving objects, too.
self.wallError = wallError
self.announce = announce
self.mapData = OccupancyGrid()
self.guesser = Guesser(self.name, self.nPoints, (0.0, 0.0, 2*math.pi),
"location",
HistogramData((self.nBins[0],self.nBins[1],1)))
self.ready_to_publish = False
self.stamp = rospy.Time.now()
def feltBump(self):
"""
Use this to signal that we've felt a bump and will shortly be contacted
about using it for a guess.
"""
self.stamp = rospy.Time.now()
self.ready_to_publish = True
def occupiedNeighbor(self, xi, yi):
"""
Returns True if one of the immediate neighbor cells is
occupied. You shouldn't expect good results if you call this
on an occupied cell.
"""
xmax = self.mapData.og.info.width
ymax = self.mapData.og.info.height
if self.mapData.sampled:
# Fails on an occupied cell
assert self.mapData.mapArrayS[xi, yi] < 50
for x in range(max(xi - 1, 0), min(xi + 1, xmax)):
for y in range(max(yi - 1, 0), min(yi + 1, ymax)):
if self.mapData.mapArrayS[x,y] > 50:
return True
return False
else:
# Fails on an occupied cell
assert self.mapData.mapArray[xi, yi] < 50
for x in range(max(xi - 1, 0), min(xi + 1, xmax)):
for y in range(max(yi - 1, 0), min(yi + 1, ymax)):
if self.mapData.mapArray[x,y] > 50:
return True
return False
def addMap(self, newMapData):
""" Receives a new map. """
assert isinstance(newMapData, MapData)
self.mapData = newMapData
def handle_guess(self, newPointList):
"""
Takes an input guess (a list of Point objects) and filters it
against a map of points that seem probable because of a recent
bump. Then resamples per usual to return a list of equally
probable points.
"""
if not self.ready_to_publish:
return False
assert isinstance(newPointList, list)
assert isinstance(newPointList[0], Point)
# Find the limits of the input data.
xmax = -1.0e6 ; ymax = -1.0e6
xmin = 1.0e6 ; ymin = 1.0e6
for pt in newPointList:
xmax = max(xmax, pt.point[0])
ymax = max(ymax, pt.point[1])
xmin = min(xmin, pt.point[0])
ymin = min(ymin, pt.point[1])
# Shrink the map to accommodate the relevant area
self.mapData.sample((xmin,ymin), (xmax,ymax))
# Cruise through the map looking for empty cells next to occupied
# ones. These will be the likely cells when a bump is encountered.
#
# Because of the possibility of bumping an object that isn't on the
# map, any empty map cell is possible. Therefore, we run through
# the map, packing the map data into a list of Point objects, since
# that's what the perfesser wants for input. While we're running
# through, we keep a separate list of empty cells next to full ones.
wallPointList = []
emptyPointList = []
for xi in range(self.mapData.ogS.info.width):
for yi in range(self.mapData.ogS.info.height):
if self.mapData.mapArrayS[xi,yi] < 50:
p = Point()
p.point = self.mapData.transform((xi, yi))
emptyPointList.append(p)
if (self.occupiedNeighbor(xi, yi)):
newP = Point()
newP.point = (p.point[0] + np.random.normal(0.0, self.mapData.ogS.info.resolution/3.0),
p.point[1] + np.random.normal(0.0, self.mapData.ogS.info.resolution/3.0),
p.point[2])
wallPointList.append(newP)
# Using the wallError, sample the two lists together to get a roughly
# correct distribution of points to feed to the perfesser.
self.mapPointList = []
for i in range(self.nPoints):
if i < self.wallError * self.nPoints:
self.mapPointList.append(random.choice(wallPointList))
else:
self.mapPointList.append(random.choice(emptyPointList))
self.guesser.newPoints(self.mapPointList)
pts = Belief()
pts.points = newPointList
self.guesser.update(pts)
self.pointList = self.guesser.outPoints()
self.ready_to_publish = False
return True
class BumpGuesser(object):
def __init__(self, name, nPoints, nBins, wallError, announce=False):
self.name = name
self.nBins = nBins
self.nPoints = nPoints
# wallError is the probability that a bump is from a feature that
# is on the map. You can bump into moving objects, too.
self.wallError = wallError
self.announce = announce
self.mapData = OccupancyGrid()
self.guesser = Guesser(
self.name,
self.nPoints,
(0.0, 0.0, 2 * math.pi),
"location",
HistogramData((self.nBins[0], self.nBins[1], 1)),
)
self.ready_to_publish = False
self.stamp = rospy.Time.now()
def feltBump(self):
"""
Use this to signal that we've felt a bump and will shortly be contacted
about using it for a guess.
"""
self.stamp = rospy.Time.now()
self.ready_to_publish = True
def occupiedNeighbor(self, xi, yi):
"""
Returns True if one of the immediate neighbor cells is
occupied. You shouldn't expect good results if you call this
on an occupied cell.
"""
xmax = self.mapData.og.info.width
ymax = self.mapData.og.info.height
if self.mapData.sampled:
# Fails on an occupied cell
assert self.mapData.mapArrayS[xi, yi] < 50
for x in range(max(xi - 1, 0), min(xi + 1, xmax)):
for y in range(max(yi - 1, 0), min(yi + 1, ymax)):
if self.mapData.mapArrayS[x, y] > 50:
return True
return False
else:
# Fails on an occupied cell
assert self.mapData.mapArray[xi, yi] < 50
for x in range(max(xi - 1, 0), min(xi + 1, xmax)):
for y in range(max(yi - 1, 0), min(yi + 1, ymax)):
if self.mapData.mapArray[x, y] > 50:
return True
return False
def addMap(self, newMapData):
""" Receives a new map. """
assert isinstance(newMapData, MapData)
self.mapData = newMapData
def handle_guess(self, newPointList):
"""
Takes an input guess (a list of Point objects) and filters it
against a map of points that seem probable because of a recent
bump. Then resamples per usual to return a list of equally
probable points.
"""
if not self.ready_to_publish:
return False
assert isinstance(newPointList, list)
assert isinstance(newPointList[0], Point)
# Find the limits of the input data.
xmax = -1.0e6
ymax = -1.0e6
xmin = 1.0e6
ymin = 1.0e6
for pt in newPointList:
xmax = max(xmax, pt.point[0])
ymax = max(ymax, pt.point[1])
xmin = min(xmin, pt.point[0])
ymin = min(ymin, pt.point[1])
# Shrink the map to accommodate the relevant area
self.mapData.sample((xmin, ymin), (xmax, ymax))
# Cruise through the map looking for empty cells next to occupied
# ones. These will be the likely cells when a bump is encountered.
#
# Because of the possibility of bumping an object that isn't on the
# map, any empty map cell is possible. Therefore, we run through
# the map, packing the map data into a list of Point objects, since
# that's what the perfesser wants for input. While we're running
# through, we keep a separate list of empty cells next to full ones.
wallPointList = []
emptyPointList = []
for xi in range(self.mapData.ogS.info.width):
for yi in range(self.mapData.ogS.info.height):
if self.mapData.mapArrayS[xi, yi] < 50:
p = Point()
p.point = self.mapData.transform((xi, yi))
emptyPointList.append(p)
if self.occupiedNeighbor(xi, yi):
newP = Point()
newP.point = (
p.point[0] + np.random.normal(0.0, self.mapData.ogS.info.resolution / 3.0),
p.point[1] + np.random.normal(0.0, self.mapData.ogS.info.resolution / 3.0),
p.point[2],
)
wallPointList.append(newP)
# Using the wallError, sample the two lists together to get a roughly
# correct distribution of points to feed to the perfesser.
self.mapPointList = []
for i in range(self.nPoints):
if i < self.wallError * self.nPoints:
self.mapPointList.append(random.choice(wallPointList))
else:
self.mapPointList.append(random.choice(emptyPointList))
self.guesser.newPoints(self.mapPointList)
pts = Belief()
pts.points = newPointList
self.guesser.update(pts)
self.pointList = self.guesser.outPoints()
self.ready_to_publish = False
return True