pycram.probabilistic_costmap

pycram.probabilistic_costmap#

Classes#

Filter

Generic enumeration.

ProbabilisticCostmap

A Costmap that uses probability distributions for representation.

Module Contents#

class pycram.probabilistic_costmap.Filter#

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

OCCUPANCY#
VISIBILITY#
class pycram.probabilistic_costmap.ProbabilisticCostmap(origin: pycram.datastructures.pose.PoseStamped, size: pint.Quantity = 2 * meter, max_cells=10000, costmap_type: typing_extensions.Type[pycram.costmaps.Costmap] = OccupancyCostmap, world: typing_extensions.Optional[pycram.datastructures.world.World] = None)#

A Costmap that uses probability distributions for representation.

x: random_events.variable.Continuous#

The variable for the x-axis (height) in meters.

y: random_events.variable.Continuous#

The variable for the y-axis (width) in meters.

costmap: pycram.costmaps.Costmap#

The legacy costmap.

origin: pycram.datastructures.pose.PoseStamped#

The origin of the costmap.

size: pint.Quantity#

The side length of the costmap. The costmap is a square.

distribution: typing_extensions.Optional[probabilistic_model.probabilistic_circuit.nx.probabilistic_circuit.ProbabilisticCircuit] = None#

The distribution associated with the costmap.

world#
property publisher#
create_event_from_map() → random_events.product_algebra.Event#
Returns:

The event that is encoded by the costmaps map.

create_distribution()#

Create a probabilistic circuit from the costmap.

sample_to_pose(sample: numpy.ndarray) → pycram.datastructures.pose.PoseStamped#

Convert a sample from the costmap to a pose.

Parameters:

sample – The sample to convert

Returns:

The pose corresponding to the sample

visualize()#

Visualize the costmap for rviz.

Contents