car_hybrid_astar — GRAPH path op

• Datenarten: image2d × matrix → table

• Aufruf: import fullseye as fs; fs.ledger.car_hybrid_astar(occupancy, poses, radius=1.0, cell=1.0, step=None, n_theta=72, allow_reverse=True, footprint=None, clearance=0.0, reverse_penalty=0.0, switch_penalty=0.0, steer_penalty=0.0, shot_every=None, max_expansions=200000, return_tree=False) (die Implementierung direkt: import carpath; carpath.car_hybrid_astar(occupancy, poses, radius=1.0, cell=1.0, step=None, n_theta=72, allow_reverse=True, footprint=None, clearance=0.0, reverse_penalty=0.0, switch_penalty=0.0, steer_penalty=0.0, shot_every=None, max_expansions=200000, return_tree=False); aus dem Register: opsgraph.get("car_hybrid_astar"))

Verwendung

> Für diesen Operator gibt es noch keine Übersetzung. Es folgt der Originaltext unverändert.

Hybrid A* (Dolgov, Thrun, Montemerlo and Diebel 2010): a car's path through an occupancy grid.

`occupancy is a 2-D grid (> 0.5 = obstacle); cell (row, col)` covers metres

`x in [col*cell, (col+1)*cell), y in [row*cell, (row+1)*cell). poses` is

`[[x, y, theta], [x', y', theta']]` (start, goal) in metres/radians. The car has minimum turning

radius `radius; footprint=(length, width, rear_offset)` is a rectangle in rear-axle coordinates

(`None = point car with clearance` metres kept from obstacles). Motion primitives are

{left, straight, right} × {forward, reverse if `allow_reverse} arcs of step` metres (default

`1.01·sqrt(2)·cell`, so each primitive leaves its cell); states are pruned per discrete cell

`(col, row, theta bin of 2π/n_theta). Cost = path length + reverse_penalty`·(reversed length)

+ `switch_penalty per gear change + steer_penalty` per steering change (all default 0, so the

cost is the geometric length). The heuristic is the obstacle-free Reeds–Shepp length (Dubins when

reversing is disallowed), admissible because every penalty is non-negative. At the start node, and then

every `shot_every expansions (default None = adaptive: a node with cost-to-go h` tries when the

expansion count is a multiple of `ceil(h / step)`, so nodes near the goal try every time, as in the

paper), the shortest analytic path from the node to the goal is collision-checked, and the search ends

when that shot is free. On an obstacle-free grid the first shot succeeds and the result equals the

Reeds–Shepp (Dubins) length exactly; with obstacles the result is never below it (`lower_bound`).

Cell pruning makes Hybrid A* an approximation of the optimum among all feasible paths, as in the paper.

Returns `points (N, 3)` poses along the path (start, tree part, analytic shot to the goal),

`length (metres), cost, lower_bound` (Reeds–Shepp/Dubins length start→goal),

`segments [(kind, gear, length)] of the whole path, n_expanded, n_generated`,

`closed_by_shot (True when the analytic expansion ended the search; False` when the goal cell

itself was popped), `shot_from (pose where the shot started), tree ((K, 3)` expanded poses,

only when `return_tree`).

Raises `ValueError: grid not 2-D or empty; poses not (2, 3)` finite, outside the grid or in

collision; `radius/cell/step not positive, n_theta < 4`, negative penalties; the goal is

unreachable (open set exhausted) or `max_expansions` was hit (reported, never a partial path).

Referenzen (Beispieldaten, Literatur)

• Katalog der Beispieldaten (Download-URLs / Lizenzen) — 2-D nutzt skimage.data (BSD/Public Domain) plus synthetische Bilder, 3-D nennt Download-URLs echter Datenquellen (Stanford, PDS, …).

• Herkunft und Literatur der Operatoren — die Quellen der Forschung/Verfahren, auf denen diese Operatorfamilie beruht.

• Der kanonische Algorithmus (Autor, Jahr) und seine Anwendungen stehen im Familienleitfaden oben.

Ausführbare Beispiele (verifizierte Samples, die diesen Operator wirklich aufrufen)

• poc_car_parking — py -3.11 examples/poc_car_parking.py

• poc_driving_school — py -3.11 examples/poc_driving_school.py

Typkompatible Folge-Operatoren (nehmen table als Eingabe)

graph_edge_consensus · graph_core_persistence · tree_morphometry · tree_sholl · tree_run_length

Gleiche Kategorie (path)

car_dubins_path · car_reeds_shepp_path


*Provenance: carpath.py — GRAPH Operator-Registry. Diese Notiz wird von tools/opdocs.py md erzeugt (nicht von Hand bearbeiten).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.