Surface and Motion Estimation from Sparse Range Data
Abstract
A system is presented for the simultaneous estimation of surface and motion parameters of a free-flying object in a telerobotics experiment. The system consists of two main components, a vision-based invariant-surface and motion estimator, and a Kalman filter. An algorithm for invariant surface and motion estimation from sparse multi-sensor range data is presented. Motion estimates from the vision module are input to a Kalman filter (KF) for tracking a 'free-flying' object in space. The predicted motion parameters from the KF are fed back to the vision module and serve as an initial guess in the search for optimal motion.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Vemuri and Skofteland. "Surface and Motion Estimation from Sparse Range Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139813Markdown
[Vemuri and Skofteland. "Surface and Motion Estimation from Sparse Range Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/vemuri1991cvpr-surface/) doi:10.1109/CVPR.1991.139813BibTeX
@inproceedings{vemuri1991cvpr-surface,
title = {{Surface and Motion Estimation from Sparse Range Data}},
author = {Vemuri, Baba C. and Skofteland, Gunleiv},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1991},
pages = {751-752},
doi = {10.1109/CVPR.1991.139813},
url = {https://mlanthology.org/cvpr/1991/vemuri1991cvpr-surface/}
}