Local GridMap

class FootprintType

rectangular = <FootprintType.rectangular: 0>

a rectangular area

circular = <FootprintType.circular: 1>

a circular are

none = <FootprintType.none: 2>

no footprint

__init__(value: int) → None

property name

Type:

str

property value

Type:

int

class LocalGridMapStateEstimation

A state estimation that integrates scans and optional odometry in a local grid map.

Uses one of the simplest mapping algorithms, following the implementation of the obstacle layer in nav2 local costmap, see ros-navigation/navigation2 d/include/nav2_costmap_2d/obstacle_layer.hpp.

1. recenter the map at the agent, setting new cells to 128 (= unknown)

2. set the footprint of the agent to 255 (= free)

3. using raycasting, for each lidar ranging measurement, sets the internal cells of the ray to 255 (= free), and the vertex of the ray (if contained in the map) to 0 (= occupied)

Registered properties:

• width (int, width)

• height (int, height)

• resolution (float, resolution) [meter / cell]

• include_transformation (bool, include_transformation)

• external_lidars (list[str], external_lidars)

• external_odometry (str, external_odometry)

• footprint (str, footprint)

__init__(lidars: list[navground.sim.LidarStateEstimation] = [], external_lidars: list[str] = [], odometry: navground.sim.OdometryStateEstimation = None, external_odometry: str = '', width: int = 10, height: int = 10, resolution: float = 0.10000000149011612, include_transformation: bool = False, footprint: navground.sim.LocalGridMapStateEstimation.FootprintType = <FootprintType.rectangular: 0>, name: str = '') → None

Constructs a new instance.

Parameters:

• lidars – The lidars sensor

• external_lidars – The name of lidars sensor

• odometry – The odometry sensor

• external_odometry – The name of odometry sensor

• width – The map width in pixels

• height – The map height in pixels

• resolution – The size of a cell in meters

• include_transformation – Whether to include the transformation between map and world frames.

• footprint – Which type of footprint to use.

• name – The name to use as a prefix

read_gridmap(state: navground.core.SensingState) → navground.core.GridMap | None

Reads a grid map from a SensingState

Calls read_gridmap_with_name, passing name.

Parameters:

state – The state

Returns:

A grid map or null if none was found.

static read_gridmap_with_name(state: navground.core.SensingState, name: str) → navground.core.GridMap | None

Reads a grid map from a SensingState

Parameters:

• state – The state

• name – The namespace of the map

Returns:

A grid map or null if none was found.

read_transform(state: navground.core.SensingState) → navground.core.Pose2 | None

Reads a transformation from a SensingState

Calls read_transform_with_name, passing name.

Parameters:

state – The state

Returns:

A pose or null if none was found.

static read_transform_with_name(state: navground.core.SensingState, name: str) → navground.core.Pose2 | None

Reads a transformation from a SensingState

Parameters:

• state – The state

• name – The namespace of the transformation

Returns:

A pose or null if none was found.

property external_lidars

Type:

list[str]

The names of the (external) lidars

property external_odometry

Type:

str

The names of the (external) odometry

property footprint

Type:

navground.sim.LocalGridMapStateEstimation.FootprintType

The footprint type

property height

Type:

int

The height of the gridmap in cells.

property include_transformation

Type:

bool

Whether to include the transformation between map and world frames.

property lidars

Type:

list[navground.sim.LidarStateEstimation]

The (external) lidars

property odometry

Type:

navground.sim.OdometryStateEstimation

The (external) odometry

property resolution

Type:

float

The size of a cell.

property width

Type:

int

The width of the gridmap in cells.