Inproceedings,
LIDAR BASED POSE TRACKING OF AN UNCOOPERATIVE SPACECRAFT USING THE SMOOTHED NORMAL DISTRIBUTION TRANSFORM
Proceedings of the 12th International Conference on Guidance, Navigation & Control Systems (GNC '23), page 1--12. Sopot, Poland, ESA, (June 2023)
Abstract
Lidar sensors provide precise 3D point cloud
measurements, and can be used for pose estima- tion
of an uncooperative satellite during space
rendezvous. For updating the estimated pose of a the
target, iterative closest point (ICP) or one of its
variants is usually applied as a tracking
method. However, for dense point clouds and space
hardware with reduced computing power, the execution
time of ICP can become a limiting factor. Normal
distribution transform (NDT) is an alternative
algorithm for fine point cloud registration, which
can be faster than ICP. Yet, NDT can be less robust
than ICP due to the discontinuities in its cost
function. This work proposes a smoothing method of
the NDT map in order to mitigate this robustness
problem. In addition, a strategy for correcting
motion blur observed with lidar sensors when
recording a tumbling target is
developed. Experiments at the European Proximity
Operations Simulator demonstrate the effi- ciency,
precision and robustness of the smoothed NDT
algorithm when compared to ICP, as well as the
importance of motion blur correction for precise
pose estimation.
