def clear_probability_from_objects(self, target, obj):
logging.info('Clearing probability from {}'.format(obj.name))
fusion_engine = self.robot.fusion_engine
vb = VariationalBayes()
if not hasattr(obj, 'relations'):
obj.define_relations()
if target is not None:
prior = fusion_engine.filters[target].probability
likelihood = obj.relations.binary_models['Inside']
mu, sigma, beta = vb.update(
measurement='Not Inside',
likelihood=likelihood,
prior=prior,
use_LWIS=False,
)
gm = GaussianMixture(beta, mu, sigma)
fusion_engine.filters[target].probability = gm
else:
# Update all but combined filters
for name, filter_ in fusion_engine.filters.iteritems():
if name == 'combined':
pass
else:
prior = filter_.probability
likelihood = obj.relations.binary_models['Inside']
mu, sigma, beta = vb.update(
measurement='Not Inside',
likelihood=likelihood,
prior=prior,
use_LWIS=False,
)
gm = GaussianMixture(beta, mu, sigma)
filter_.probability = gm
def __init__(self,
robot_pose=(0, 0, 0),
visible=True,
default_color=cnames['yellow'],
element_dict={},
min_view_dist=0.3,
max_view_dist=1.0):
self.element_dict = element_dict
# Define nominal viewcone
self.min_view_dist = min_view_dist # [m]
self.max_view_dist = max_view_dist # [m]
self.view_angle = math.pi / 2 # [rad]
viewcone_pts = [
(0, 0),
(self.max_view_dist * math.cos(self.view_angle / 2),
self.max_view_dist * math.sin(self.view_angle / 2)),
(self.max_view_dist * math.cos(-self.view_angle / 2),
self.max_view_dist * math.sin(-self.view_angle / 2)),
(0, 0),
]
# Create SoftMax model for camera
self.detection_model = camera_model_2D(self.min_view_dist,
self.max_view_dist)
# Instantiate Sensor superclass object
update_rate = 1 # [hz]
has_physical_dimensions = True
super(Camera, self).__init__(update_rate, has_physical_dimensions)
# Set the ideal and actual viewcones
self.ideal_viewcone = MapObject(
'Ideal viewcone',
viewcone_pts,
visible=False,
blocks_camera=False,
color_str='pink',
pose=robot_pose,
has_relations=False,
centroid_at_origin=False,
)
self.viewcone = MapObject(
'Viewcone',
viewcone_pts,
alpha=0.2,
visible=True,
blocks_camera=False,
color_str='lightyellow',
pose=robot_pose,
has_relations=False,
centroid_at_origin=False,
)
self.view_pose = (0, 0, 0)
# <>TODO: Add in and test an offset of (-0.1,-0.1)
self.offset = (0, 0, 0) # [m] offset (x,y,theta) from center of robot
self._move_viewcone(robot_pose)
# Set up the VB fusion parameters
self.vb = VariationalBayes()
def __init__(self,
map_=None,
web_interface_topic='python',
false_alarm_prob=0.2):
self.update_rate = None
self.has_physical_dimensions = False
self.speed_model = speed_model()
self.false_alarm_prob = false_alarm_prob
super(Human, self).__init__(self.update_rate,
self.has_physical_dimensions)
# self.certainties = ['think', 'know']
self.certainties = ['know']
self.positivities = ['is not',
'is'] # <>TODO: oh god wtf why does order matter
self.relations = {
'object': [
'behind',
'in front of',
'left of',
'right of',
'near',
],
'area': ['inside', 'near', 'outside']
}
self.movement_types = ['moving', 'stopped']
self.movement_qualities = ['slowly', 'moderately', 'quickly']
self.groundings = {}
self.groundings['area'] = map_.areas
self.groundings['object'] = {}
for cop_name, cop in map_.cops.iteritems():
# if cop.has_relations:
self.groundings['object'][cop_name] = cop
for object_name, obj in map_.objects.iteritems():
if obj.has_relations:
self.groundings['object'][object_name] = obj
self.target_names = ['nothing', 'a robot'] + map_.robbers.keys()
self.utterance = ''
self.new_update = False
# Set up the VB fusion parameters
self.vb = VariationalBayes()
if web_interface_topic != 'python':
# Subscribe to web interface
print web_interface_topic
import rospy
from std_msgs.msg import String
rospy.Subscriber(web_interface_topic, String, self.callback)
