Johnny Fernandes
100 lines
3.5 KiB
Python
100 lines
3.5 KiB
Python
"""World geometry and robot specs.
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All coordinates are in meters. (0, 0) is the centre of the field, +x is
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east, +y is north. Z is up but unused here. These constants must match
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``worlds/field.wbt`` and the proto files; if the world changes, change
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this file and only this file.
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Pen layout (post-refactor)
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--------------------------
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The pen is *external* to the field, accessed through a 3 m gate cut into
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the south stone wall at y = -15. Sheep entering through the gate end up
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in a fenced rectangle south of the field; the dog stays in the field
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(soft-limited above DOG_SOUTH_LIMIT during training and inference).
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field +y north
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+-----------+
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| ...... |
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+---||||----+ y = -15 (south wall, gate at x ∈ [10, 13])
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||||
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|pen| y ∈ [-22, -15]
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+---+
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"""
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import math
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# --- Field (square, stone-walled) ---
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FIELD_X = (-15.0, 15.0)
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FIELD_Y = (-15.0, 15.0)
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# Conservative inside bounds — sheep/dog should not graze the wall.
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FIELD_INSIDE_MARGIN = 0.5
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# --- Pen (external, south of the field) ---
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PEN_X = (10.0, 13.0)
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PEN_Y = (-22.0, -15.0)
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PEN_CENTER = (0.5 * (PEN_X[0] + PEN_X[1]), 0.5 * (PEN_Y[0] + PEN_Y[1]))
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# The point the dog drives the flock toward: the gate centre on the field side.
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PEN_ENTRY = (0.5 * (PEN_X[0] + PEN_X[1]), -15.0)
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# --- Gate (the hole in the south stone wall) ---
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GATE_X = PEN_X
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GATE_Y = -15.0
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# --- Robot specs (must match proto files) ---
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# Dog (controllers/shepherd_dog/, protos/ShepherdDog.proto)
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DOG_WHEEL_RADIUS = 0.038 # m
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DOG_WHEEL_BASE = 0.28 # m, axle-to-axle
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DOG_MAX_WHEEL_OMEGA = 70.0 # rad/s
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DOG_MAX_LINEAR = DOG_WHEEL_RADIUS * DOG_MAX_WHEEL_OMEGA # ~2.66 m/s
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# Sheep (controllers/sheep/, protos/Sheep.proto)
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SHEEP_WHEEL_RADIUS = 0.031 # m
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SHEEP_WHEEL_BASE = 0.20 # m
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SHEEP_MAX_WHEEL_OMEGA = 25.0 # rad/s
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SHEEP_MAX_LINEAR = SHEEP_WHEEL_RADIUS * SHEEP_MAX_WHEEL_OMEGA # ~0.78 m/s
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# --- Webots step ---
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WEBOTS_DT = 0.016 # seconds, matches WorldInfo.basicTimeStep = 16 in field.wbt
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# --- Dog "virtual south wall" (training keeps dog out of the pen) ---
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# At inference the controller also clips to this so a slightly miscalibrated
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# policy doesn't accidentally drive into the pen and trap the sheep.
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DOG_SOUTH_LIMIT = -14.5
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# --- Maximum supported flock size ---
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MAX_SHEEP = 10
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def in_pen(x: float, y: float) -> bool:
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"""True if (x, y) lies inside the external pen rectangle."""
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return PEN_X[0] < x < PEN_X[1] and PEN_Y[0] < y < PEN_Y[1]
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def in_field(x: float, y: float, margin: float = 0.0) -> bool:
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return (FIELD_X[0] + margin <= x <= FIELD_X[1] - margin
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and FIELD_Y[0] + margin <= y <= FIELD_Y[1] - margin)
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def in_gate_corridor(x: float, y: float, margin: float = 0.0) -> bool:
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"""True if (x, y) lies in the column of the gate (between field and pen)."""
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return (PEN_X[0] - margin <= x <= PEN_X[1] + margin
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and PEN_Y[0] - margin <= y <= GATE_Y + margin)
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def is_penned_position(x: float, y: float, latch_margin: float = 0.2) -> bool:
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"""A sheep latches to "penned" once it crosses the gate plane south.
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True iff x is inside the gate column (with a small margin) AND
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y has dipped below the gate line. Once latched, the sheep is held by
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in-pen forces and will not exit on its own.
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"""
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return (PEN_X[0] - latch_margin <= x <= PEN_X[1] + latch_margin
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and y <= GATE_Y)
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def distance_to_pen_entry(x: float, y: float) -> float:
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return math.hypot(x - PEN_ENTRY[0], y - PEN_ENTRY[1])
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