warehouse_grid — DRIVE `agv` op

• Data kinds: none → any (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.warehouse_grid(n_rack_rows=3, n_rack_cols=4, rack_len=4, aisle=1, margin=2) (to call the implementation directly, import agvfleet; agvfleet.warehouse_grid(n_rack_rows=3, n_rack_cols=4, rack_len=4, aisle=1, margin=2); from the registry, opsdrive.get("warehouse_grid"))

• GPU: none (CPU reference implementation only)

Usage

Warehouse grid made of shelf rows and aisles (True = drivable).

A shelf is a horizontal block of 1 row x rack_len squares, surrounded by aisles of width aisle on the top, bottom, left and right. margin around the perimeter Place the square running zone (in front of the station). The return is (grid, info), where info has a list of racks, racks, and the shape of the grid.

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_agv_fleet — py -3.11 examples/poc_agv_fleet.py

Ops the type connects to (they accept `any` as input)

course_crank · course_s_curve · course_turnaround · course_slope · course_intersection · course_parallel_parking · course_crossing · course_road

Same category (`agv`)

grid_distances · mapf_cbs · mapf_ecbs · mapf_joint_astar · mapf_prioritized · plan_conflicts · plan_cost · adg_build

*Provenance: agvfleet.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

warehouse_grid — DRIVE agv op