A Model-Based 3D Template Matching Technique for Pose Acquisition of an Uncooperative Space Object

Abstract

This paper presents a customized three-dimensional template matching technique for autonomous pose determination of uncooperative targets. This topic is relevant to advanced space applications, like active debris removal and on-orbit servicing. The proposed technique is model-based and produces estimates of the target pose without any prior pose information, by processing three-dimensional point clouds provided by a LIDAR. These estimates are then used to initialize a pose tracking algorithm. Peculiar features of the proposed approach are the use of a reduced number of templates and the idea of building the database of templates on-line, thus significantly reducing the amount of on-board stored data with respect to traditional techniques. An algorithm variant is also introduced aimed at further accelerating the pose acquisition time and reducing the computational cost. Technique performance is investigated within a realistic numerical simulation environment comprising a target model, LIDAR operation and various target-chaser relative dynamics scenarios, relevant to close-proximity flight operations. Specifically, the capability of the proposed techniques to provide a pose solution suitable to initialize the tracking algorithm is demonstrated, as well as their robustness against highly variable pose conditions determined by the relative dynamics. Finally, a criterion for autonomous failure detection of the presented techniques is presented.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor

“…However, there is drifting phenomenon of the detected center owning by the ATM algorithm based on the ground-truth center in each frame. Many previous studies [ 50 , 51 , 52 , 53 , 54 , 55 ] used template matching which has shown a large drifting phenomenon that significantly affects the tracking performance over long term. The reason for this is that during landing as the marker becomes bigger, its appearance changes rapidly, so the new (updated) template cannot keep up and therefore, in the long run, the tracking results deteriorate.…”

H ∞ LIDAR odometry for spacecraft relative navigation

“…The advantage of 3D LIDAR compared to its 2D counterpart (visual and IR) is operating during day and night, being independent of the target's thermal properties and capable of revealing the underlying structure of an object [17]. Despite current literature offering quite a few LIDAR based relative navigation solutions [7][8][9][10][11][12][13][14][15][16], these present the following deficiencies: First, they rely on the Iterative Closest Point (ICP) [18] method that may settle the estimated rigid body transformation solution in a locally rather than a globally optimum solution. Second, current algorithms require an off-line training process that exploits a 3D model of the expected Target platform.…”

Adaptive pose and inertial parameters estimation of free-floating tumbling space objects using dual vector quaternions

“…In addition, uncooperative targets are tumbling in space, which also bring challenges for the AR&D. Consequently, the vision-based sensors are widely used in this field to obtain the relative pose measurements, which are further utilized to output the pose estimation Northwestern Polytechnical University, Xi'an, China of the uncooperative targets by image processing techniques. [5][6][7] However, these methods do not take the kinematics and dynamics of the space objects into account, which results in huge computational burden and disregard of the space environment. Also, the methods merely rely on the image processing techniques, so they can only estimate the pose parameters.…”