| Alternate document: Details Thin Junction Tree Filters for (03) Mark A. Paskin |
Mark A. Paskin  Home/Search
Context Related
| berkeley.edu/~paskin/...Paskin2003a.pdf Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: berkeley.edu/~paskin/pubs...index (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: Simultaneous Localization and Mapping (SLAM) is a fundamental problem in mobile robotics: while a robot navigates in an unknown environment, it must incrementally build a map of its surroundings and, at the same time, localize itself within that map. One popular solution is to treat SLAM as an estimation problem and apply the Kalman filter; this approach is elegant, but it does not scale well: the size of the belief state and the time complexity of the filter update both grow... (Update)
Cited by: More
Bounding Uncertainty in EKF-SLAM: - The Robocentric Local (Correct)
Landmark Selection for Vision-Based Navigation - Pablo Sala Student (2006) (Correct)
Distributed Localization of Networked Cameras - Stanislav Funiak Carlos (2006) (Correct)
Active bibliography (related documents): More All
0.6: Thin Junction Tree Filters for Simultaneous Localization and.. - Paskin (Correct)
0.4: Thin Junction Tree Filters for . . . - Paskin (2003) (Correct)
0.3: Simultaneous Localization and Mapping - Mark Paskin Report (Correct)
Similar documents based on text: More All
0.3: Grammatical Bigrams - Paskin (2001) (Correct)
0.3: Sample Propagation - Paskin (2003) (Correct)
0.2: Cubic-time Parsing and Learning Algorithms for Grammatical Bigram .. - Paskin (2001) (Correct)
Related documents from co-citation: More All
12: FastSLAM: A factored solution to the simultaneous localization and mapping probl.. - Montemerlo, Thrun et al. - 2002
9: An atlas framework for scalable mapping - Bosse, Newman et al. - 2002
8: Simultaneous mapping and localization with sparse extended information filters - Thrun, Koller et al. - 2002
BibTeX entry: (Update)
M.A. Paskin. Thin junction tree filters for simultaneous localization and mapping. IJCAI-03. http://citeseer.ist.psu.edu/paskin03thin.html More
@misc{ paskin-thin,
author = "M. Paskin",
title = "Thin junction tree filters for simultaneous localization and mapping",
text = "M.A. Paskin. Thin junction tree filters for simultaneous localization and
mapping. IJCAI-03.",
url = "citeseer.ist.psu.edu/paskin03thin.html" }
Citations (may not include all citations):144 Probabilistic Networks and Expert Systems (context) - Cowell, Dawid et al. - 1999
113 Tractable inference for complex stochastic processes - Boyen, Koller - 1998
99 Estimating uncertain spatial relationships in robotics (context) - Smith, Self et al. - 1990
55 FastSLAM: A factored solution to the simultaneous localizati.. - Montemerlo, Thrun et al. - 2002
44 Robotic mapping: A survey - Thrun - 2002
23 Thin junction tree filters for simultaneous localization and.. - Paskin - 2002
15 Exploiting the architecture of dynamic systems - Boyen, Koller - 1999
11 Gaussian markov distributions over finite graphs (context) - Speed, Kiiveri - 1986
11 Simultaneous localization and mapping with sparse extended i.. (context) - Thrun, Koller et al. - 2002
9 Clustering without (context) - Draper - 1995
5 Probabilistic map learning: Necessity and difficulties (context) - ebert, e-Brezetz et al. - 1996
The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.cs.berkeley.edu/~paskin/pubs/index.html): More
Sample Propagation - Paskin (2003) (Correct)
Robust Probabilistic Inference in Distributed Systems - Mark Paskin Computer (2004) (Correct)
Thin Junction Tree Filters for . . . - Paskin (2003) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC