roverslip op• Data kinds: table × signal → table
• Call: import fullseye as fs; fs.ledger.slip_predict(model, slopes, level: 'float' = 0.9) -> 'dict' (to call the implementation directly, import roverslip; roverslip.slip_predict(model, slopes, level: 'float' = 0.9) -> 'dict'; from the registry, opsdrive.get("slip_predict"))
Slip-ratio prediction and a two-sided level band. For the Gaussian process, the predictive distribution of observations (latent variance + noise); for quantile regression, the curves themselves.
> The detailed description below is the original text — the summary and the headings are translated.
返り値 {"mean", "std", "lower", "upper", "median", "level"}(各 (n,))。分位点回帰の mean は当てはめた分位点の平均、std は四分位範囲 / 1.349、帯の端は (1 ± level)/2 の分位点(当てはめた段に無ければ ValueError)に、共形の補正(slip_quantile_fit の conformal)があればその幅を足す。
• 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.
• poc_rover_slip_risk_path — py -3.11 examples/poc_rover_slip_risk_path.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
roverslip)bekker_pressure · bekker_wheel_sinkage · wheel_forces · wheel_sinkage · wheel_traction_curve · slope_slip_curve · ground_shift_track · odometry_slip
*Provenance: roverslip.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.