The autonomous close-in maneuvering necessary for the rendezvous and docking of two spacecraft requires a relative navigation sensor system that can determine the relative position and orientation (pose) of the controlled spacecraft with respect to the target spacecraft. Lidar imaging systems offer the potential for accurately measuring the relative six degree-of-freedom positions and orientations and the associated rates.
In this paper, we present simulation results generated using a high fidelity modeling program. A simulated lidar system is used to capture close-proximity range images of a model target spacecraft, producing 3-D point cloud data. The sequentially gathered point-clouds are compared with the previous point-cloud using a real-time point-plane correspondence-less variant of the Iterative Closest Points (ICP) algorithm. The resulting range and pose estimates are used in turn to prime the next time-step iteration of the ICP algorithm. Results from detailed point-plane simulations and will be presented. The implications for real-time implementation are discussed.
In recent years, NASA's interest in autonomous rendezvous and docking operations with impaired or non-cooperative spacecraft has grown extensively. In order to maneuver and dock, a servicing spacecraft must be able to determine the relative 6 degree-of-freedom (6 DOF) motion between the vehicle and the target spacecraft. One method to determine the relative 6 DOF position and attitude is through lidar imaging. A flash lidar sensor system can capture close-proximity range images of the target spacecraft, producing 3-D point cloud data sets. These sequentially collected point-cloud data sets can be compared to a point cloud image of the target at a known location using a point correspondence-less variant of the Iterative Closest Points (ICP) algorithm to determine the relative 6 DOF displacements. Simulation experiments indicate that the MSE, angular error, mean, and standard deviations for position and orientation estimates did not vary as a function of position and attitude. Furthermore, the computational times required by this algorithm were comparable to previously reported variants of the point-to-point and point-to-plane based ICP variants.