Update move_to_pose for cases where alpha > pi/2 or alpha < -pi/2

Author: Aglargil

Control/move_to_pose/move_to_pose.py

@@ -5,15 +5,21 @@
 Author: Daniel Ingram (daniel-s-ingram)
         Atsushi Sakai (@Atsushi_twi)
         Seied Muhammad Yazdian (@Muhammad-Yazdian)
+        Wang Zheng (@Aglargil)
 
 P. I. Corke, "Robotics, Vision & Control", Springer 2017, ISBN 978-3-319-54413-7
 
 """
 
 import matplotlib.pyplot as plt
 import numpy as np
-from random import random
+import sys
+import pathlib
+
+sys.path.append(str(pathlib.Path(__file__).parent.parent.parent))
 from utils.angle import angle_mod
+from random import random
+
 
 class PathFinderController:
     """
@@ -71,13 +77,18 @@ def calc_control_command(self, x_diff, y_diff, theta, theta_goal):
         # from 0 rad to 2*pi rad with slight turn
 
         rho = np.hypot(x_diff, y_diff)
-        alpha = angle_mod(np.arctan2(y_diff, x_diff) - theta)
-        beta = angle_mod(theta_goal - theta - alpha)
         v = self.Kp_rho * rho
-        w = self.Kp_alpha * alpha - self.Kp_beta * beta
 
+        alpha = angle_mod(np.arctan2(y_diff, x_diff) - theta)
+        beta = angle_mod(theta_goal - theta - alpha)
         if alpha > np.pi / 2 or alpha < -np.pi / 2:
+            # recalculate alpha to make alpha in the range of [-pi/2, pi/2]
+            alpha = angle_mod(np.arctan2(-y_diff, -x_diff) - theta)
+            beta = angle_mod(theta_goal - theta - alpha)
+            w = self.Kp_alpha * alpha - self.Kp_beta * beta
             v = -v
+        else:
+            w = self.Kp_alpha * alpha - self.Kp_beta * beta
 
         return rho, v, w
 
@@ -111,8 +122,7 @@ def move_to_pose(x_start, y_start, theta_start, x_goal, y_goal, theta_goal):
         x_diff = x_goal - x
         y_diff = y_goal - y
 
-        rho, v, w = controller.calc_control_command(
-            x_diff, y_diff, theta, theta_goal)
+        rho, v, w = controller.calc_control_command(x_diff, y_diff, theta, theta_goal)
 
         if abs(v) > MAX_LINEAR_SPEED:
             v = np.sign(v) * MAX_LINEAR_SPEED
@@ -126,10 +136,22 @@ def move_to_pose(x_start, y_start, theta_start, x_goal, y_goal, theta_goal):
 
         if show_animation:  # pragma: no cover
             plt.cla()
-            plt.arrow(x_start, y_start, np.cos(theta_start),
-                      np.sin(theta_start), color='r', width=0.1)
-            plt.arrow(x_goal, y_goal, np.cos(theta_goal),
-                      np.sin(theta_goal), color='g', width=0.1)
+            plt.arrow(
+                x_start,
+                y_start,
+                np.cos(theta_start),
+                np.sin(theta_start),
+                color="r",
+                width=0.1,
+            )
+            plt.arrow(
+                x_goal,
+                y_goal,
+                np.cos(theta_goal),
+                np.sin(theta_goal),
+                color="g",
+                width=0.1,
+            )
             plot_vehicle(x, y, theta, x_traj, y_traj)
 
 
@@ -144,16 +166,16 @@ def plot_vehicle(x, y, theta, x_traj, y_traj):  # pragma: no cover
     p2 = np.matmul(T, p2_i)
     p3 = np.matmul(T, p3_i)
 
-    plt.plot([p1[0], p2[0]], [p1[1], p2[1]], 'k-')
-    plt.plot([p2[0], p3[0]], [p2[1], p3[1]], 'k-')
-    plt.plot([p3[0], p1[0]], [p3[1], p1[1]], 'k-')
+    plt.plot([p1[0], p2[0]], [p1[1], p2[1]], "k-")
+    plt.plot([p2[0], p3[0]], [p2[1], p3[1]], "k-")
+    plt.plot([p3[0], p1[0]], [p3[1], p1[1]], "k-")
 
-    plt.plot(x_traj, y_traj, 'b--')
+    plt.plot(x_traj, y_traj, "b--")
 
     # for stopping simulation with the esc key.
     plt.gcf().canvas.mpl_connect(
-        'key_release_event',
-        lambda event: [exit(0) if event.key == 'escape' else None])
+        "key_release_event", lambda event: [exit(0) if event.key == "escape" else None]
+    )
 
     plt.xlim(0, 20)
     plt.ylim(0, 20)
@@ -162,26 +184,31 @@ def plot_vehicle(x, y, theta, x_traj, y_traj):  # pragma: no cover
 
 
 def transformation_matrix(x, y, theta):
-    return np.array([
-        [np.cos(theta), -np.sin(theta), x],
-        [np.sin(theta), np.cos(theta), y],
-        [0, 0, 1]
-    ])
+    return np.array(
+        [
+            [np.cos(theta), -np.sin(theta), x],
+            [np.sin(theta), np.cos(theta), y],
+            [0, 0, 1],
+        ]
+    )
 
 
 def main():
-
     for i in range(5):
         x_start = 20.0 * random()
         y_start = 20.0 * random()
         theta_start: float = 2 * np.pi * random() - np.pi
         x_goal = 20 * random()
         y_goal = 20 * random()
         theta_goal = 2 * np.pi * random() - np.pi
-        print(f"Initial x: {round(x_start, 2)} m\nInitial y: {round(y_start, 2)} m\nInitial theta: {round(theta_start, 2)} rad\n")
-        print(f"Goal x: {round(x_goal, 2)} m\nGoal y: {round(y_goal, 2)} m\nGoal theta: {round(theta_goal, 2)} rad\n")
+        print(
+            f"Initial x: {round(x_start, 2)} m\nInitial y: {round(y_start, 2)} m\nInitial theta: {round(theta_start, 2)} rad\n"
+        )
+        print(
+            f"Goal x: {round(x_goal, 2)} m\nGoal y: {round(y_goal, 2)} m\nGoal theta: {round(theta_goal, 2)} rad\n"
+        )
         move_to_pose(x_start, y_start, theta_start, x_goal, y_goal, theta_goal)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()