Point clouds

Declaration

Each LiDAR or radar is one channel of foxglove.PointCloud messages, declared in the overlay’s point_clouds array with its kind, which a PointCloud message cannot carry:

"point_clouds": [
  {"channel": "/lidar/top",   "name": "lidar_top",   "kind": "lidar"},
  {"channel": "/radar/front", "name": "radar_front", "kind": "radar"}
]

Field	Type	Required	Rule
`channel`	string	yes	The sensor’s channel.
`name`	string	yes	Non-empty, unique among point clouds.
`kind`	`"lidar"` \| `"radar"`	yes	The sensor type.

Fields

Field	Requirement
`x`, `y`, `z`	MUST be present, metres.
`intensity`	SHOULD be included when the sensor provides it.
`ring` (beam index)	SHOULD be included when the sensor provides it. Required for a LiDAR-only recording; see below.
`red`, `green`, `blue`, or one packed `rgb` / `rgba`	MAY be included for per-point colour.
anything else (`rcs`, `vx`, `vy`, …)	MAY be included; kept as published.

Include intensity and ring whenever you have them. They cost only storage, and they cannot be added later without re-uploading.

Frames

Every LiDAR cloud is placed in the vehicle frame (x forward, y left, z up, z = 0 at the ground). Choose one of two shapes per cloud, by the message’s frame_id:

`frame_id`	Meaning	Requirement
`"vehicle"`	Points are already in the vehicle frame.	Used as is.
`"<sensor>"`	Points are in the sensor’s own frame.	A `foxglove.FrameTransform` with `parent_frame_id: "vehicle"` and `child_frame_id: "<sensor>"` MUST be present. Positions are transformed once: `p_vehicle = R · p_sensor + t`.

A sensor-frame cloud without a transform is rejected, never used as is: a transform applied twice, or not at all, produces a plausible-looking and entirely wrong cloud. Positions, vectors and scalars transform differently, and mixing them up is silent:

positions (x, y, z) rotate, then translate;
velocities and directions (e.g. radar vx, vy) rotate only. Only positions are transformed at ingest, so publish per-point vectors already in the vehicle frame;
scalars (intensity, ring, rcs) are frame-invariant and pass through.

A sensor with no elevation channel (most automotive radar) shows a constant z equal to its mounting height after transformation. That is correct.

Several LiDARs

Publish either one already-merged LiDAR in the vehicle frame, or one channel per sensor in its own frame with its transform. Several lidar channels are merged by frame index: frame i of every sensor forms one cloud. Per-sensor channels MUST therefore be index-aligned: the same number of frames, frame i of each covering the same sweep. Unequal counts are merged up to the shortest channel, with a warning.

LiDAR-only recordings

A recording with no camera is valid when its first declared lidar carries x, y, z and ring: the LiDAR is rendered as a range-image video (one row per beam), which becomes the recording’s video. A recording with no camera and a LiDAR without ring is rejected, with an error naming the missing field. See A recording must have a video.

Nomadic MCAP Specification

Examples

Declaration

Fields

Frames

Several LiDARs

LiDAR-only recordings

​Declaration

​Fields

​Frames

​Several LiDARs

​LiDAR-only recordings

Declaration

Fields

Frames

Several LiDARs

LiDAR-only recordings