Files
PythonRobotics/PathPlanning/FrenetOptimalTrajectory/frenet_optimal_trajectory.py
2018-01-10 16:22:10 -08:00

106 lines
2.3 KiB
Python

"""
Frenet optimal trajectory generator
author: Atsushi Sakai (@Atsushi_twi)
"""
import numpy as np
import matplotlib.pyplot as plt
class quinic_polynomial:
def __init__(self, xs, vxs, axs, xe, vxe, axe, T):
# calc coefficient of quinic polynomial
self.xs = xs
self.vxs = vxs
self.axs = axs
self.xe = xe
self.vxe = vxe
self.axe = axe
self.a0 = xs
self.a1 = vxs
self.a2 = axs / 2.0
A = np.array([[T**3, T**4, T**5],
[3 * T ** 2, 4 * T ** 3, 5 * T ** 4],
[6 * T, 12 * T ** 2, 20 * T ** 3]])
b = np.array([xe - self.a0 - self.a1 * T - self.a2 * T**2,
vxe - self.a1 - 2 * self.a2 * T,
axe - 2 * self.a2])
x = np.linalg.solve(A, b)
self.a3 = x[0]
self.a4 = x[1]
self.a5 = x[2]
def calc_point(self, t):
xt = self.a0 + self.a1 * t + self.a2 * t**2 + \
self.a3 * t**3 + self.a4 * t**4 + self.a5 * t**5
return xt
def calc_first_derivative(self, t):
xt = self.a1 + 2 * self.a2 * t + \
3 * self.a3 * t**2 + 4 * self.a4 * t**3 + 5 * self.a5 * t**4
return xt
def calc_second_derivative(self, t):
xt = 2 * self.a2 + 6 * self.a3 * t + 12 * self.a4 * t**2 + 20 * self.a5 * t**3
return xt
max_speed = 15.0 / 3.6
def frenet_optimal_planning():
maxd = 5.0
dd = 1.0
dt = 1.0
T = 10.0
max_s = max_speed * T
ds = 10.0
target_speed = 5.0 / 3.6
for di in np.arange(-maxd, maxd, dd):
for Ti in np.arange(dt, T, dt):
lat_qp = quinic_polynomial(0.0, 0.0, 0.0, di, 0.0, 0.0, Ti)
time = []
d = []
for t in np.arange(0.0, Ti, 0.1):
time.append(t)
d.append(lat_qp.calc_point(t))
for si in np.arange(ds, max_s, ds):
lon_qp = quinic_polynomial(
0.0, 0.0, 0.0, si, target_speed, 0.0, Ti)
s = []
for t in time:
s.append(lon_qp.calc_point(t))
plt.plot(s, d)
# plt.plot(d)
def main():
print(__file__ + " start!!")
frenet_optimal_planning()
plt.axis("equal")
plt.show()
if __name__ == '__main__':
main()