Complexity Analysis and Efficient Measurement Selection Primitives for High-Rate Graph SLAM
Name
1709.06821.pdf
Description
Submitted version
Size
1.69 MB
Format
Adobe PDF
Checksum (MD5)
1c501b96c5596d3a95501b83c6878953
Author(s)
Frey, Kristoffer M.
Steiner, Ted J.
How, Jonathan P.
Date Issued
March 2018
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Frey, Kristoffer M., Steiner, Ted J. and How, Jonathan P. 2018. "Complexity Analysis and Efficient Measurement Selection Primitives for High-Rate Graph SLAM."
Version
Original manuscript
Abstract
© 2018 IEEE. Sparsity has been widely recognized as crucial for efficient optimization in graph-based SLAM. Because the sparsity and structure of the SLAM graph reflect the set of incorporated measurements, many methods for sparsification have been proposed in hopes of reducing computation. These methods often focus narrowly on reducing edge count without regard for structure at a global level. Such structurally-naïve techniques can fail to produce significant computational savings, even after aggressive pruning. In contrast, simple heuristics such as measurement decimation and keyframing are known empirically to produce significant computation reductions. To demonstrate why, we propose a quantitative metric called elimination complexity (EC) that bridges the existing analytic gap between graph structure and computation. EC quantifies the complexity of the primary computational bottleneck: the factorization step of a Gauss-Newton iteration. Using this metric, we show rigorously that decimation and keyframing impose favorable global structures and therefore achieve computation reductions on the order of r2/9 and r3, respectively, where r is the pruning rate. We additionally present numerical results showing EC provides a good approximation of computation in both batch and incremental (iSAM2) optimization and demonstrate that pruning methods promoting globally-efficient structure outperform those that do not.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICRA.2018.8460708
