DSOL: A Fast Direct Sparse Odometry Scheme

Chao Qu; Shreyas S. Shivakumar; Ian D. Miller; Camillo J. Taylor

IROS 2022poster12 citations

DSOL: A Fast Direct Sparse Odometry Scheme

Chao Qu, Shreyas S. Shivakumar, Ian D. Miller, Camillo J. Taylor

Abstract

In this paper, we describe Direct Sparse Odometry Lite (DSOL), an improved version of Direct Sparse Odometry (DSO) [1]. We propose several algorithmic and implementation enhancements which speed up computation by a significant factor (on average 5x) even on resource-constrained platforms. The increase in speed allows us to process images at higher frame rates, which in turn provides better results on rapid motions. Our open-source implementation is available at https://github.com/versatran01/dso1.

BibTeX

@inproceedings{iros2022_dsolafastdirects,
  title = {DSOL: A Fast Direct Sparse Odometry Scheme},
  author = {Chao Qu and Shreyas S. Shivakumar and Ian D. Miller and Camillo J. Taylor},
  booktitle = {IROS 2022},
  year = {2022}
}