lateral op• Data kinds: any → table
• Call: import fullseye as fs; fs.ledger.stanley_steer(front_pose, path, *, gain: 'float', speed, softening: 'float' = 0.0, max_steer: 'float' = inf, start_index=None, window: 'int' = 40) -> 'Dict[str, np.ndarray]' (to call the implementation directly, import drivelateral; drivelateral.stanley_steer(front_pose, path, *, gain: 'float', speed, softening: 'float' = 0.0, max_steer: 'float' = inf, start_index=None, window: 'int' = 40) -> 'Dict[str, np.ndarray]'; from the registry, opsdrive.get("stanley_steer"))
Stanley steering angle δ = ψ_e + atan2(−k e, k_s + v) (the lateral offset e of the front-axle center is positive to the left of the path; ψ_e = path heading − ψ).
front_pose: (3,) or (N, 3). Clipped by max_steer (clipping departs from the closed form of stanley_straight_decay). Return value: steer, lateral, heading_error, index.
Raises ValueError: wrong shape, k ≤ 0, v < 0, k_s < 0, max_steer ≤ 0.
• 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.
• gallery_drive_lateral_env — py -3.11 examples/gallery_drive_lateral_env.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
lateral)friction_circle_usage · curve_speed_limit · design_min_radius · understeer_gradient · steady_cornering · bicycle_model_step · ackermann_steer_angles · offtracking_circle
*Provenance: drivelateral.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.