Exactly sparse delayed-state filters for view-based SLAM
MetadataShow full item record
KeywordInformation filters; Kalman filtering; Machine vision; Mobile robot motion planning; Mobile robots; Recursive estimation; Robot vision systems; Simultaneous localization and mapping; Underwater vehicles
This paper reports the novel insight that the simultaneous localization and mapping (SLAM) information matrix is exactly sparse in a delayed-state framework. Such a framework is used in view-based representations of the environment that rely upon scan-matching raw sensor data to obtain virtual observations of robot motion with respect to a place it has previously been. The exact sparseness of the delayed-state information matrix is in contrast to other recent feature-based SLAM information algorithms, such as sparse extended information filter or thin junction-tree filter, since these methods have to make approximations in order to force the feature-based SLAM information matrix to be sparse. The benefit of the exact sparsity of the delayed-state framework is that it allows one to take advantage of the information space parameterization without incurring any sparse approximation error. Therefore, it can produce equivalent results to the full-covariance solution. The approach is validated experimentally using monocular imagery for two datasets: a test-tank experiment with ground truth, and a remotely operated vehicle survey of the RMS Titanic.
Author Posting. © IEEE, 2006. This article is posted here by permission of IEEE for personal use, not for redistribution. The definitive version was published in IEEE Transactions on Robotics 22 (2006): 1110-1114, doi:10.1109/TRO.2006.886264.
Suggested CitationArticle: Eustice, Ryan M., Singh, Hanumant, Leonard, John J., "Exactly sparse delayed-state filters for view-based SLAM", IEEE Transactions on Robotics 22 (2006): 1100-1114, DOI:10.1109/TRO.2006.886264, https://hdl.handle.net/1912/1411
Showing items related by title, author, creator and subject.
Eustice, Ryan M.; Pizarro, Oscar; Singh, Hanumant (IEEE, 2008-04)As autonomous underwater vehicles (AUVs) are becoming routinely used in an exploratory context for ocean science, the goal of visually augmented navigation (VAN) is to improve the near-seafloor navigation precision of such ...
Grasshopper DCMD : an undergraduate electrophysiology lab for investigating single-unit responses to behaviorally-relevant stimuli Nguyen, Dieu My T.; Roper, Mark; Mircic, Stanislav; Olberg, Robert M.; Gage, Gregory J. (Faculty of Undergraduate Neuroscience, 2017-05)Avoiding capture from a fast-approaching predator is an important survival skill shared by many animals. Investigating the neural circuits that give rise to this escape behavior can provide a tractable demonstration of ...
To be seen or to hide : visual characteristics of body patterns for camouflage and communication in the Australian giant cuttlefish Sepia apama Zylinski, S.; How, M. J.; Osorio, D.; Hanlon, Roger T.; Marshall, N. J. (University of Chicago, 2011-04-06)It might seem obvious that a camouflaged animal must generally match its background whereas to be conspicuous an organism must differ from the background. However, the image parameters (or statistics) that evaluate the ...