Robotics

Point cloud

Definition

A point cloud is a collection of points representing sampled locations in space, usually with three-dimensional coordinates. Individual points may also carry attributes such as color or return intensity.

Also known as: Point clouds

Updated

Spatial samples from sensors

A depth camera or lidar can produce measurements that become points in a shared coordinate frame. Ouster's explanation describes this process for laser range measurements. The Point Cloud Library documentation describes point clouds as collections whose point type determines the stored data.

For a humanoid reaching toward a table, a cloud can represent the visible tabletop and objects on it. These samples can support geometric processing without already identifying which object is a cup or where it should be grasped.

Organized and unorganized clouds

An organized cloud preserves rows and columns, often corresponding to a depth image. An unorganized cloud is simply a collection of samples without that image arrangement. PCL documents both forms and explains why neighboring pixel relationships can make processing organized clouds more efficient.

A cloud is not a solid model

Points do not automatically define connected surfaces, occupied volumes, or object identities. Missing or invalid coordinates also need handling; PCL distinguishes clouds containing only finite data from those with invalid values. Converting a cloud into a mesh, an occupancy grid, or a distance field requires additional assumptions and processing.

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