Frames, units and time | Docs

Mismatched conventions are the most common reason robot data quietly fails: a quaternion read in the wrong order or a flipped camera frame trains a model on wrong data without any error. Rayform converts every recording to one convention on the way in, records it in the metadata, and converts again on the way out only when you ask.

Space

Item	Convention
World frame	One per site. Right-handed, Z up, metres (ROS REP-103)
Camera frame	OpenCV: X right, Y down, Z forward
Rotations	Unit quaternions, `w, x, y, z` order
Poses	`[x, y, z, qw, qx, qy, qz]`, child in parent
Camera model	Pinhole with radial-tangential distortion, from a versioned calibration

Time

Item	Convention
Timestamps	`int64` nanoseconds (`t_ns`), monotonic within a session
Clock	The session clock; offsets estimated during alignment are already applied
Resampling	Only on request, with the method recorded (`nearest` or `linear`)

Values

Quantity	Unit and type
RGB images	`uint8`, channels-last on disk, channels-first in `EpisodeDataset`
Depth	metres, `float32`; missing depth is `0`
Point clouds	metres, `float32`, in the sensor frame
Joint positions	radians (revolute) or metres (prismatic), `float32`
Joint velocities	per second, `float32`
Gripper	as reported by your robot; units stored in channel metadata

Converting on the way out

Exports, streams and the PyTorch dataset accept frame and quat_order:

`frame`	World	Camera
`rayform` (default)	Z up	OpenCV
`ros`	Z up, REP-103	ROS optical (same axes as OpenCV)
`opencv`	Y down	OpenCV
`opengl`	Y up	OpenGL: X right, Y up, Z backward
`isaac`	Z up	USD camera (OpenGL axes)
`mujoco`	Z up	MuJoCo camera (OpenGL axes)

Python

seg.channel("poses/base", frame="opengl")
client.exports.create(slice_, format="rlds", options={"frame": "ros", "quat_order": "xyzw"})

Provenance

Every exported sample carries slice, segment, segment_version and site. Keep them in your training logs; any result can then be traced to the exact data it came from.