Publication Details
Efficient Implementation for Block Matrix Operations Nonlinear Least Squares Problems for Robotic Applications
Ila Viorela Simona, Ph.D.
Šolony Marek, Ing., Ph.D. (DCGM)
Zemčík Pavel, prof. Dr. Ing., dr. h. c. (DCGM)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM)
Block Matrix Operations, Nonlinear Least Squares, SLAM, Robotics
A large number of robotic, computer vision and computer graphics applications rely on efficiently solving the associated sparse linear system. Simultaneous localization and mapping (SLAM), structure from motion (SFM), non-rigid shape recovery, elastodynamic simulations, are only few examples in this direction. In general, those problems are non-linear and the solution can be approximated by incrementally solving a series of linearized problems. In some applications, the size of the systems might considerable affect the performance, especially when the sparsity is low. This paper exploits the block structure of such problems and offers efficient solutions to manipulate block matrices. In particular, we focus on testing the method on SLAM applications, but the applicability of the technique remains general.
@inproceedings{BUT103427,
author="Lukáš {Polok} and Viorela Simona {Ila} and Marek {Šolony} and Pavel {Zemčík} and Pavel {Smrž}",
title="Efficient Implementation for Block Matrix Operations Nonlinear Least Squares Problems for Robotic Applications",
booktitle="Proceedings of 2013 IEEE International Conference on Robotics and Automation",
year="2013",
pages="123--131",
publisher="IEEE Computer Society",
address="Karlsruhe",
doi="10.1109/ICRA.2013.6630883",
isbn="978-1-4673-5642-8",
url="http://ieeexplore.ieee.org/document/6630883/?arnumber=6630883"
}