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https://github.com/AtsushiSakai/PythonRobotics.git
synced 2026-01-14 20:28:13 -05:00
code clean up
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@@ -55,14 +55,11 @@ def calc_dynamic_window(x, config):
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x[3] + config.max_accel * config.dt,
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x[4] - config.max_dyawrate * config.dt,
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x[4] + config.max_dyawrate * config.dt]
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# print(Vs, Vd)
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# [vmin,vmax, yawrate min, yawrate max]
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dw = [max(Vs[0], Vd[0]), min(Vs[1], Vd[1]),
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max(Vs[2], Vd[2]), min(Vs[3], Vd[3])]
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#print(dw)
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return dw
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@@ -76,7 +73,6 @@ def calc_trajectory(xinit, v, y, config):
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traj = np.vstack((traj, x))
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time += config.dt
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# print(len(traj))
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return traj
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@@ -98,7 +94,7 @@ def calc_final_input(x, u, dw, config, goal, ob):
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speed_cost = config.speed_cost_gain * \
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(config.max_speed - traj[-1, 3])
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ob_cost = calc_obstacle_cost(traj, ob, config)
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#print(ob_cost)
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# print(ob_cost)
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final_cost = to_goal_cost + speed_cost + ob_cost
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@@ -110,9 +106,6 @@ def calc_final_input(x, u, dw, config, goal, ob):
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min_u = [v, y]
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best_traj = traj
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# print(min_u)
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# input()
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return min_u, best_traj
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@@ -144,8 +137,8 @@ def calc_to_goal_cost(traj, goal, config):
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goal_magnitude = math.sqrt(goal[0]**2 + goal[1]**2)
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traj_magnitude = math.sqrt(traj[-1, 0]**2 + traj[-1, 1]**2)
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dot_product = (goal[0]*traj[-1, 0]) + (goal[1]*traj[-1, 1])
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error = dot_product / (goal_magnitude*traj_magnitude)
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dot_product = (goal[0] * traj[-1, 0]) + (goal[1] * traj[-1, 1])
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error = dot_product / (goal_magnitude * traj_magnitude)
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error_angle = math.acos(error)
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cost = config.to_goal_cost_gain * error_angle
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@@ -197,7 +190,7 @@ def main():
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x = motion(x, u, config.dt)
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traj = np.vstack((traj, x)) # store state history
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#print(traj)
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# print(traj)
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if show_animation:
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plt.cla()
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@@ -218,7 +211,9 @@ def main():
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print("Done")
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if show_animation:
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plt.plot(traj[:, 0], traj[:, 1], "-r")
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plt.show()
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plt.pause(0.0001)
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plt.show()
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if __name__ == '__main__':
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