Precise pose estimation of the NASA Mars 2020 Perseverance rover through a stereo-vision-based approach

Visual Odometry (VO) is a fundamental technique to enhance the navigation capabilities of planetary exploration rovers. By processing the images acquired during the motion, VO methods provide estimates of the relative position and attitude between navigation steps with the detection and tracking of two-dimensional (2D) image keypoints. This method allows one to mitigate trajectory inconsistencies associated with slippage conditions resulting from dead-reckoning techniques. We present here an independent analysis of the high-resolution stereo images of the NASA Mars 2020 Perseverance rover to retrieve its accurate localization on sols 65, 66, 72, and 120. The stereo pairs are processed by using a 3D-to-3D stereo-VO approach that is based on consolidated techniques and accounts for the main nonlinear optical effects characterizing real cameras. The algorithm is first validated through the analysis of rectified stereo images acquired by the NASA Mars Exploration Rover Opportunity, and then applied to the determination of Perseverance's path. The results suggest that our reconstructed path is consistent with the telemetered trajectory, which was directly retrieved onboard the rover's system. The estimated pose is in full agreement with the archived rover's position and attitude after short navigation steps. Significant differences (similar to 10-30 cm) between our reconstructed and telemetered trajectories are observed when Perseverance traveled distances larger than 1m between the acquisition of stereo pairs.

Automated summary

Visual Odometry is a fundamental technique used to enhance the navigation capabilities of planetary exploration rovers. By processing the images acquired during motion, it provides estimates of the relative position and attitude between navigation steps. In this study, an independent analysis of high-resolution stereo images of the NASA Mars 2020 Perseverance rover was conducted to accurately determine its localization. The results show that the reconstructed path is consistent with the telemetered trajectory.