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@ -286,7 +286,11 @@ class sprint(gym.Env):
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x = np.random.uniform(x_range[0], x_range[1])
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y = np.random.uniform(y_range[0], y_range[1])
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if np.linalg.norm(np.array([x, y]) - self.Gen_player_pos[:2]) < 5:
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dir_x = (x - self.Gen_player_pos[0]) / abs (x - self.Gen_player_pos[0])
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dir_y = (y - self.Gen_player_pos[1]) / abs (y - self.Gen_player_pos[1])
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x = x + 5 * dir_x
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y = y + 5 * dir_y
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self.walk_target = np.array([x, y])
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def step(self, action):
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@ -336,7 +340,7 @@ class sprint(gym.Env):
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robot_speed = r.loc_torso_velocity[0]
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direction_error = abs(self.walk_rel_orientation)
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direction_error = min(direction_error, 10)
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reward = robot_speed * (3 - 0.5 * direction_error / 10)
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reward = robot_speed * (1.5 - direction_error / 10)
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if self.walk_distance < 1:
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reward += 20
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self.generate_random_target()
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