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https://github.com/AtsushiSakai/PythonRobotics.git
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162 lines
3.6 KiB
Python
162 lines
3.6 KiB
Python
"""
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Path tracking simulation with pure pursuit steering control and PID speed control.
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author: Atsushi Sakai
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"""
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import numpy as np
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import math
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import matplotlib.pyplot as plt
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k = 0.1 # look forward gain
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Lfc = 1.0 # look-ahead distance
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Kp = 1.0 # speed propotional gain
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dt = 0.1 # [s]
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L = 2.9 # [m] Tread of vehicle
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show_animation = True
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class State:
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def __init__(self, x=0.0, y=0.0, yaw=0.0, v=0.0):
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self.x = x
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self.y = y
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self.yaw = yaw
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self.v = v
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def update(state, a, delta):
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state.x = state.x + state.v * math.cos(state.yaw) * dt
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state.y = state.y + state.v * math.sin(state.yaw) * dt
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state.yaw = state.yaw + state.v / L * math.tan(delta) * dt
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state.v = state.v + a * dt
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return state
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def PIDControl(target, current):
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a = Kp * (target - current)
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return a
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def pure_pursuit_control(state, cx, cy, pind):
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ind = calc_target_index(state, cx, cy)
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if pind >= ind:
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ind = pind
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if ind < len(cx):
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tx = cx[ind]
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ty = cy[ind]
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else:
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tx = cx[-1]
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ty = cy[-1]
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ind = len(cx) - 1
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alpha = math.atan2(ty - state.y, tx - state.x) - state.yaw
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if state.v < 0: # back
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alpha = math.pi - alpha
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Lf = k * state.v + Lfc
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delta = math.atan2(2.0 * L * math.sin(alpha) / Lf, 1.0)
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return delta, ind
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def calc_target_index(state, cx, cy):
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# search nearest point index
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dx = [state.x - icx for icx in cx]
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dy = [state.y - icy for icy in cy]
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d = [abs(math.sqrt(idx ** 2 + idy ** 2)) for (idx, idy) in zip(dx, dy)]
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ind = d.index(min(d))
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L = 0.0
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Lf = k * state.v + Lfc
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# search look ahead target point index
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while Lf > L and (ind + 1) < len(cx):
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dx = cx[ind + 1] - cx[ind]
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dy = cx[ind + 1] - cx[ind]
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L += math.sqrt(dx ** 2 + dy ** 2)
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ind += 1
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return ind
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def main():
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# target course
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cx = np.arange(0, 50, 0.1)
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cy = [math.sin(ix / 5.0) * ix / 2.0 for ix in cx]
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target_speed = 10.0 / 3.6 # [m/s]
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T = 100.0 # max simulation time
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# initial state
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state = State(x=-0.0, y=-3.0, yaw=0.0, v=0.0)
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lastIndex = len(cx) - 1
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time = 0.0
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x = [state.x]
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y = [state.y]
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yaw = [state.yaw]
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v = [state.v]
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t = [0.0]
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target_ind = calc_target_index(state, cx, cy)
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while T >= time and lastIndex > target_ind:
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ai = PIDControl(target_speed, state.v)
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di, target_ind = pure_pursuit_control(state, cx, cy, target_ind)
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state = update(state, ai, di)
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time = time + dt
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x.append(state.x)
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y.append(state.y)
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yaw.append(state.yaw)
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v.append(state.v)
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t.append(time)
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if show_animation:
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plt.cla()
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plt.plot(cx, cy, ".r", label="course")
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plt.plot(x, y, "-b", label="trajectory")
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plt.plot(cx[target_ind], cy[target_ind], "xg", label="target")
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plt.axis("equal")
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plt.grid(True)
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plt.title("Speed[km/h]:" + str(state.v * 3.6)[:4])
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plt.pause(0.001)
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# Test
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assert lastIndex >= target_ind, "Cannot goal"
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if show_animation:
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plt.plot(cx, cy, ".r", label="course")
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plt.plot(x, y, "-b", label="trajectory")
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plt.legend()
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plt.xlabel("x[m]")
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plt.ylabel("y[m]")
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plt.axis("equal")
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plt.grid(True)
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flg, ax = plt.subplots(1)
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plt.plot(t, [iv * 3.6 for iv in v], "-r")
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plt.xlabel("Time[s]")
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plt.ylabel("Speed[km/h]")
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plt.grid(True)
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plt.show()
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if __name__ == '__main__':
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print("Pure pursuit path tracking simulation start")
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main()
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