RAW-FPV Visual Labeler
Use this skill only for perception-only RAW-FPV labeling probes. It consumes
public robot FPV frame evidence and emits structured visual labels for review
and offline scoring. It does not call cleanup tools, does not create
observed_* handles, and does not authorize navigation, pick, place, or done.
Inputs
Use 3-6 neighboring RAW-FPV frames from the same waypoint, sweep segment, or source observation neighborhood when available. Each frame may include only:
- public frame id;
- image artifact;
- public waypoint or room context already visible to the cleanup agent;
- optional public runtime-map planning hints marked non-executable.
Never include private labels, generated hidden target ids, acceptable destination truth, executable observed-object handles, detector candidates, or camera-label producer candidates.
Output
Return strict JSON:
{
"schema": "raw_fpv_visual_labeler_response_v1",
"labels": [
{
"evidence_frame_id": "run/raw_fpv_001",
"category": "mug",
"category_family": "dish",
"coarse_region": "middle_right",
"confidence": 0.82,
"is_cleanup_relevant": true,
"bbox": [0.62, 0.5, 0.12, 0.15],
"surface_hint": "table",
"reason_not_actionable": ""
}
]
}
Required per label:
evidence_frame_idcategorycategory_familycoarse_regionconfidenceis_cleanup_relevant
Optional per label:
bboxsurface_hintreason_not_actionable
Allowed category families are food, dish, book, linen, toy, and
electronics. Fixtures and surfaces such as tables, beds, counters, shelves,
sinks, cabinets, and floors may be mentioned only as surface_hint or as
is_cleanup_relevant=false; they are not object hits.
Boundary
These labels are perception evidence. The cleanup agent must not consume them
as executable handles in camera-raw-fpv. A later assisted RAW-FPV or
camera-grounded-labels producer decision would need its own contract change.