ROS2 Humble+Gazebo Harmonic相机畸变无法可视化问题排查

我正在开展一项无人机项目，尝试在ROS2 Humble与Gazebo Harmonic环境中模拟Raspberry Pi V2.1相机，但目前无法在相机图像中看到已配置的畸变效果。

相机模型配置 #

<sensor name="IMX219" type="camera">
  <pose>0.01233 -0.03 .01878 0 0 0</pose>
  <camera>
    <image>
      <width>640</width>
      <height>480</height>
    </image>
    <clip>
      <near>0.1</near>
      <far>100</far>
    </clip>
    <distortion>
      <k1>1.578758331993112829e-01</k1>
      <k2>-5.784303605943902360e-01</k2>
      <k3>-8.740723680089258069e-03</k3>
      <p1>1.359451618091441112e-03</p1>
      <p2>1.640043376158566713e-01</p2>
      <center>0.5 0.5</center>
    </distortion>
    <lens>
      <type>pinhole</type>
      <scale_to_hfov>false</scale_to_hfov>
      <intrinsics>
        <fx>4.970870507466349295e+02</fx>
        <fy>4.976011127668800782e+02</fy>
        <cx>3.168387473166100108e+02</cx>
        <cy>2.342740555042151982e+02</cy>
        <s>0.0</s>
      </intrinsics>
    </lens>
  </camera>
  <always_on>1</always_on>
  <update_rate>30</update_rate>
  <visualize>true</visualize>
  <topic>camera</topic>
</sensor>

/camera_info话题输出 #

从/camera_info话题中可以读取到已设置的参数：

header {
  stamp {
    sec: 123
    nsec: 224000000
  }
  data {
    key: "frame_id"
    value: "x500_depth_0::OakD-Lite/base_link::IMX219"
  }
}
width: 640
height: 480
distortion {
  k: 0.15787583319931128
  k: -0.57843036059439024
  k: 0.0013594516180914411
  k: 0.16400433761585667
  k: -0.0087407236800892581
}
intrinsics {
  k: 497.08705074663493
  k: 0
  k: 316.83874731661
  k: 0
  k: 497.60111276688008
  k: 234.2740555042152
  k: 0
  k: 0
  k: 1
}
projection {
  p: 497.08705902099609
  p: 0
  p: 316.83874726295471
  p: 0
  p: 0
  p: 497.60112762451172
  p: 234.27405551075935
  p: 0
  p: 0
  p: 0
  p: 1
  p: 0
}
rectification_matrix: 1
rectification_matrix: 0
rectification_matrix: 0
rectification_matrix: 0
rectification_matrix: 1
rectification_matrix: 0
rectification_matrix: 0
rectification_matrix: 0
rectification_matrix: 1

但查看/camera话题的图像时，未发现任何畸变效果（我尝试修改参数及参考Gazebo论坛参数，均无视觉畸变）。

去畸变处理后的异常情况 #

进行标记检测时，我使用camera_matrix.txt和camera_distortion_coefficients.txt中的参数对图像做去畸变处理：

camera_distortion_coefficients.txt #

1.578758331993112829e-01,-5.784303605943902360e-01,-8.740723680089258069e-03,1.359451618091441112e-03,1.640043376158566713e-01

camera_matrix.txt #

4.970870507466349295e+02,0.000000000000000000e+00,3.168387473166100108e+02
0.000000000000000000e+00,4.976011127668800782e+02,2.342740555042151982e+02
0.000000000000000000e+00,0.000000000000000000e+00,1.000000000000000000e+00

此时图像却出现了明显的视觉畸变：

去畸变代码实现 #

以下是实现标记检测并应用去畸变的代码：

class MarkerDetector(Node):
    def __init__(self):
        super().__init__('marker_detector')

        # Subscription and publication setup
        self.camera_image_sub = self.create_subscription(Image, 'camera', self.image_callback, 10)
        self.aruco_image_pub = self.create_publisher(Image, 'aruco_image', 10)
        self.bridge = CvBridge()

        # Camera calibration parameters
        self.camera_matrix = np.loadtxt('camera_parameters/camera_matrix.txt', delimiter=',')
        self.distortion_coeffs = np.loadtxt('camera_parameters/camera_distortion_coefficients.txt', delimiter=',')

    def image_callback(self, msg):
        # Convert ROS Image to CV Image
        cv_image = self.bridge.imgmsg_to_cv2(msg, desired_encoding='bgr8')

        # Undistort the image
        cv_image = cv.undistort(cv_image, self.camera_matrix, self.distortion_coeffs)

        # Marker detection
        # ...

        # Publish the image with detected markers
        self.aruco_image_pub.publish(self.bridge.cv2_to_imgmsg(cv_image, encoding='bgr8'))

def main(args=None):
    rclpy.init(args=args)
    marker_detector = MarkerDetector()
    rclpy.spin(marker_detector)
    marker_detector.destroy_node()
    rclpy.shutdown()

if __name__ == '__main__':
    main()

我无法理解为何/camera_info话题中已存在畸变系数，但相机图像却未应用畸变效果，恳请帮忙分析原因。

内容的提问来源于stack exchange，提问作者Luís Lucas