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rover_function.py
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rover_function.py
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from rover_utils import RoverDomain, PointBSpline, ConstObstacleCost, NegGeom, AABoxes, UnionGeom, AdditiveCosts, \
ConstCost
import numpy as np
def create_cost_small():
c = np.array([[0.11353145, 0.17251116],
[0.4849413, 0.7684513],
[0.38840863, 0.10730809],
[0.32968556, 0.37542275],
[0.64342773, 0.32438415],
[0.42, 0.35],
[0.38745546, 0.0688907],
[0.05771529, 0.1670573],
[0.48750001, 0.67864249],
[0.5294646, 0.66245226],
[0.88495861, 0.76770809],
[0.71132462, 0.46580745],
[0.02038182, 0.32146063],
[0.34077448, 0.70446464],
[0.61490175, 0.79081785],
[0.37367616, 0.6720441],
[0.14711569, 0.57060365],
[0.76084188, 0.65168123],
[0.51038721, 0.78655373],
[0.50396508, 0.90299952],
[0.23763956, 0.38260748],
[0.40169679, 0.72553068],
[0.59670114, 0.08541569],
[0.5514408, 0.62855134],
[0.84606733, 0.94264543],
[0.8, 0.19590218],
[0.39181603, 0.46357532],
[0.44800403, 0.27380116],
[0.5681913, 0.1468706],
[0.37418262, 0.69210095]])
l = c - 0.05
h = c + 0.05
r_box = np.array([[0.5, 0.5]])
r_l = r_box - 0.5
r_h = r_box + 0.5
trees = AABoxes(l, h)
r_box = NegGeom(AABoxes(r_l, r_h))
obstacles = UnionGeom([trees, r_box])
start = np.zeros(2) + 0.05
goal = np.array([0.95, 0.95])
costs = [ConstObstacleCost(obstacles, cost=20.), ConstCost(0.05)]
cost_fn = AdditiveCosts(costs)
return cost_fn, start, goal
def create_small_domain():
cost_fn, start, goal = create_cost_small()
n_points = 10
traj = PointBSpline(dim=2, num_points=n_points)
n_params = traj.param_size
domain = RoverDomain(cost_fn,
start=start,
goal=goal,
traj=traj,
s_range=np.array([[-0.1, -0.1], [1.1, 1.1]]))
return domain
def create_cost_large():
c = np.array([[0.43143755, 0.20876147],
[0.38485367, 0.39183579],
[0.02985961, 0.22328303],
[0.7803707, 0.3447003],
[0.93685657, 0.56297285],
[0.04194252, 0.23598362],
[0.28049582, 0.40984475],
[0.6756053, 0.70939481],
[0.01926493, 0.86972335],
[0.5993437, 0.63347932],
[0.57807619, 0.40180792],
[0.56824287, 0.75486851],
[0.35403502, 0.38591056],
[0.72492026, 0.59969313],
[0.27618746, 0.64322757],
[0.54029566, 0.25492943],
[0.30903526, 0.60166842],
[0.2913432, 0.29636879],
[0.78512072, 0.62340245],
[0.29592116, 0.08400595],
[0.87548394, 0.04877622],
[0.21714791, 0.9607346],
[0.92624074, 0.53441687],
[0.53639253, 0.45127928],
[0.99892031, 0.79537837],
[0.84621631, 0.41891986],
[0.39432819, 0.06768617],
[0.92365693, 0.72217512],
[0.95520914, 0.73956575],
[0.820383, 0.53880139],
[0.22378049, 0.9971974],
[0.34023233, 0.91014706],
[0.64960636, 0.35661133],
[0.29976464, 0.33578931],
[0.43202238, 0.11563227],
[0.66764947, 0.52086962],
[0.45431078, 0.94582745],
[0.12819915, 0.33555344],
[0.19287232, 0.8112075],
[0.61214791, 0.71940626],
[0.4522542, 0.47352186],
[0.95623345, 0.74174186],
[0.17340293, 0.89136853],
[0.04600255, 0.53040724],
[0.42493468, 0.41006649],
[0.37631485, 0.88033853],
[0.66951947, 0.29905739],
[0.4151516, 0.77308712],
[0.55762991, 0.26400156],
[0.6280609, 0.53201974],
[0.92727447, 0.61054975],
[0.93206587, 0.42107549],
[0.63885574, 0.37540613],
[0.15303425, 0.57377797],
[0.8208471, 0.16566631],
[0.14889043, 0.35157346],
[0.71724622, 0.57110725],
[0.32866327, 0.8929578],
[0.74435871, 0.47464421],
[0.9252026, 0.21034329],
[0.57039306, 0.54356078],
[0.56611551, 0.02531317],
[0.84830056, 0.01180542],
[0.51282028, 0.73916524],
[0.58795481, 0.46527371],
[0.83259048, 0.98598188],
[0.00242488, 0.83734691],
[0.72505789, 0.04846931],
[0.07312971, 0.30147979],
[0.55250344, 0.23891255],
[0.51161315, 0.46466442],
[0.802125, 0.93440495],
[0.9157825, 0.32441602],
[0.44927665, 0.53380074],
[0.67708372, 0.67527231],
[0.81868924, 0.88356194],
[0.48228814, 0.88668497],
[0.39805433, 0.99341196],
[0.86671752, 0.79016975],
[0.01115417, 0.6924913],
[0.34272199, 0.89543756],
[0.40721675, 0.86164495],
[0.26317679, 0.37334193],
[0.74446787, 0.84782643],
[0.55560143, 0.46405104],
[0.73567977, 0.12776233],
[0.28080322, 0.26036748],
[0.17507419, 0.95540673],
[0.54233783, 0.1196808],
[0.76670967, 0.88396285],
[0.61297539, 0.79057776],
[0.9344029, 0.86252764],
[0.48746839, 0.74942784],
[0.18657635, 0.58127321],
[0.10377802, 0.71463978],
[0.7771771, 0.01463505],
[0.7635042, 0.45498358],
[0.83345861, 0.34749363],
[0.38273809, 0.51890558],
[0.33887574, 0.82842507],
[0.02073685, 0.41776737],
[0.68754547, 0.96430979],
[0.4704215, 0.92717361],
[0.72666234, 0.63241306],
[0.48494401, 0.72003268],
[0.52601215, 0.81641253],
[0.71426732, 0.47077212],
[0.00258906, 0.30377501],
[0.35495269, 0.98585155],
[0.65507544, 0.03458909],
[0.10550588, 0.62032937],
[0.60259145, 0.87110846],
[0.04959159, 0.535785]])
l = c - 0.025
h = c + 0.025
r_box = np.array([[0.5, 0.5]])
r_l = r_box - 0.5
r_h = r_box + 0.5
trees = AABoxes(l, h)
r_box = NegGeom(AABoxes(r_l, r_h))
obstacles = UnionGeom([trees, r_box])
start = np.zeros(2) + 0.05
goal = np.array([0.95, 0.95])
costs = [ConstObstacleCost(obstacles, cost=20.), ConstCost(0.05)]
cost_fn = AdditiveCosts(costs)
return cost_fn, start, goal
def create_large_domain(force_start=False,
force_goal=False,
start_miss_cost=None,
goal_miss_cost=None):
cost_fn, start, goal = create_cost_large()
n_points = 30
traj = PointBSpline(dim=2, num_points=n_points)
n_params = traj.param_size
domain = RoverDomain(cost_fn,
start=start,
goal=goal,
traj=traj,
start_miss_cost=start_miss_cost,
goal_miss_cost=goal_miss_cost,
force_start=force_start,
force_goal=force_goal,
s_range=np.array([[-0.1, -0.1], [1.1, 1.1]]))
return domain
def main():
def l2cost(x, point):
return 10 * np.linalg.norm(x - point, 1)
domain = create_large_domain(force_start=False,
force_goal=False,
start_miss_cost=l2cost,
goal_miss_cost=l2cost)
n_points = domain.traj.npoints
raw_x_range = np.repeat(domain.s_range, n_points, axis=1)
from ebo_core.helper import ConstantOffsetFn, NormalizedInputFn
# maximum value of f
f_max = 5.0
f = ConstantOffsetFn(domain, f_max)
f = NormalizedInputFn(f, raw_x_range)
x_range = f.get_range()
x = np.random.uniform(x_range[0], x_range[1])
print('Input = {}'.format(x))
print('Output = {}'.format(f(x)))
if __name__ == "__main__":
main()