mapf_cbs — DRIVE `agv` op

• Data kinds: image2d → table

• Call: import fullseye as fs; fs.ledger.mapf_cbs(grid, starts, goals, max_nodes=20000, horizon=None) (to call the implementation directly, import agvfleet; agvfleet.mapf_cbs(grid, starts, goals, max_nodes=20000, horizon=None); from the registry, opsdrive.get("mapf_cbs"))

Usage

Conflict-Based Search (Sharon, Stern, Felner, Sturtevant 2015). A collision-free plan with optimal sum of costs.

> The detailed description below is the original text — the summary and the headings are translated.

上段は「衝突を 1 つ選び、2 台のどちらかに制約を足す」二分木の最良優先探索、下段は 1 台の時空間 A*。返りは dict: paths(各車両のマスの列)、cost(sum of costs)、nodes(展開した節の数)、solved。節の上限に達したら solved=False(黙って最適でない解を返さない)。

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 `table` as input)

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (`agv`)

warehouse_grid · grid_distances · 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).*

mapf_cbs — DRIVE agv op