Real-time Wide-depth-range Pose Estimation with Laser Scanning Point Cloud

In this work, a real-time wide depth pose estimation method with laser scanning point cloud is proposed. Unlike other 6D pose estimation methods, the proposed method can maintain a robust and accurate tracking performance even when the target spacecraft has an obvious transformation in depth. To make full use of the known model, a pose estimation network based on CNNs is established to estimate the position. After the point cloud is translated according to the estimation result, the quaternion of the target is calculated independently. To evaluate the consequent of the network, we simulated the scanning point cloud with a wide depth range. The results show that the proposed method has strong robustness to the depth transformation and higher computational efficiency.