version: "1.0.0" name: object-localization description: Locate visible object points in the robot's frame from the current observation, choosing the method the observation profile allows (depth with camera geometry, RGB with camera geometry, or RGB with measured robot motion only). Use before choosing any approach, grasp, placement or drive target, and again after anything moved.

Object localization

Ground every target in the current observation. Never reuse pixels or positions after the camera, the robot base or the object moved, and never replace missing geometry with guessed coordinates. Fill in the robot's facts in This robot; the methods below are the same everywhere.

Pixels

• Select pixels in the original, full-resolution image of the current observation, not

in a downscaled preview or a composed video; convert preview pixels with the scale the reply gives.

• Pick several pixels inside the object's visible surface, away from edges, shadows and

occluders: edge pixels take the depth of the background.

• Prefer features that look distinct from every view (tips, corners, marks); symmetric

features are easy to mismatch between views.

Choose the method

Depth and camera geometry. Back-project pixels with <pixel_to_position> (or with the depth image, intrinsics and camera pose in your own code, references/geometry.md). Discard points with invalid or sparse depth, or far from the others. Cross-check from a second view or camera before a precise action; disagreement beyond the robot's tolerance means a wrong pixel, so reselect rather than average.

RGB with camera geometry. One pixel gives a ray, not a point. Either intersect the ray with a known plane (a support surface of known height; use the object's contact point with it, not its top), or triangulate the same physical feature from two camera positions far enough apart that the rays meet at a wide angle with a small gap. Check an estimate by projecting it back into a new image where the robot offers that.

RGB only, no camera geometry. Images give directions, not metric positions. Learn how the image maps to robot motion by moving an empty gripper a small, known displacement and watching its visible feature. Align the same gripper feature with the target in fresh images from more than one view, with small motions near a safe height. One image's overlap does not prove alignment or contact (parallax); confirm in a second view or after a small motion. A learned mapping holds only near that height, orientation and camera.

Use the result carefully

• A localized point is a visible surface point, not an object centre, pose, grasp or

clearance. Average several top-surface points for a centre, offset toward the centre by about half the object's thickness for a grasp, and choose approach offsets from current evidence.

• Close views resolve far more detail than overview cameras; get one with

camera-inspection for contact-critical targets, or confirm by touch where the robot senses force.

• Record in memory what you localized against, the views and the method, not one

layout's coordinates.

This robot