GRID Docs | General Robotics

from grid_types import PointCloud

A class to represent a point cloud.

Fields

np.ndarray

Array of points with shape (N, D) where N is the number of points and D is the dimensionality of each point (e.g., D=3 for x,y,z). Each row is a point, and each column is a dimension/feature.

List[str]

List of field names for the point cloud data. The order of field names must correspond to the columns in the points array. If not provided, defaults to [‘x’, ‘y’] for 2D points (N,2) or [‘x’, ‘y’, ‘z’] for 3D points (N,3). For other dimensions, fields must be explicitly provided.

Timestamp from the sensor or transport message, in nanoseconds in source_clock. This is provenance, not necessarily comparable to the local system clock.

Unix timestamp in nanoseconds recorded when this process received the complete transport message.

Monotonic timestamp in nanoseconds recorded at the same receipt event. It is comparable only when monotonic_clock_id matches the consumer’s clock domain.

Stable identifier for the monotonic clock domain, normally the Linux boot ID. A proxy crossing machines must restamp the receipt or leave this metadata absent.

Receiver-local message identity. Drivers that provide this increment it once for every newly received message, so repeated reads of the same cloud retain the same value.

Coordinate frame containing points.

Non-negative upper bound, in seconds, on the time spanned by the points in this cloud.

Name of the source_timestamp_ns clock domain, such as "ros" or "device".

Constructor

Signature

PointCloud(
    points: np.ndarray,
    fields: Optional[List[str]] = None,
    source_timestamp_ns: Optional[int] = None,
    received_timestamp_ns: Optional[int] = None,
    received_monotonic_ns: Optional[int] = None,
    monotonic_clock_id: Optional[str] = None,
    sequence_id: Optional[int] = None,
    frame_id: Optional[str] = None,
    acquisition_duration_s: Optional[float] = None,
    source_clock: Optional[str] = None,
)

Methods

`from_dict()`

Signature

from_dict(data: dict) -> PointCloud

Deserialize from dictionary

`to_dict()`

Signature

to_dict() -> dict

Serialize to dictionary for JSON transfer

Example

import numpy as np
# 3D points with x, y, z
points_data_3d = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
pc1 = PointCloud(points=points_data_3d)
print(pc1.points)
print(pc1.fields)
# 2D points with x, y
points_data_2d = np.array([[1, 2], [3, 4]], dtype=np.float32)
pc2 = PointCloud(points=points_data_2d)
print(pc2.fields)
# 3D points with custom fields (e.g., x, y, intensity)
points_data_custom = np.array([[10, 20, 100], [30, 40, 150]], dtype=np.float32)
pc3 = PointCloud(points=points_data_custom, fields=['x', 'y', 'intensity'])
print(pc3.fields)
# Points with x, y, z, r, g, b
points_rgb = np.array([[1,2,3, 255,0,0], [4,5,6, 0,255,0]], dtype=np.float32)
fields_rgb = ['x', 'y', 'z', 'r', 'g', 'b']
pc4 = PointCloud(points=points_rgb, fields=fields_rgb)
print(pc4.points.shape)
print(pc4.fields)

​Fields

​Constructor

​Methods

​from_dict()

​to_dict()

​Example

Fields

Constructor

Methods

`from_dict()`

`to_dict()`

Example