• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 119
Next 10 →

The SLAM project: debugging system software via static analysis

by Thomas Ball, Sriram K. Rajamani - SIGPLAN Not
"... Abstract. The goal of the SLAM project is to check whether or not a program obeys "API usage rules " that specif[y what it means to be a good client of an API. The SLAM toolkit statically analyzes a C program to determine whether or not it violates given usage rules. The toolkit has two un ..."
Abstract - Cited by 472 (17 self) - Add to MetaCart
unique aspects: it does not require the programmer to annotate the source program (invariants are inferred); it minimizes noise (false error messages) through a process known as "counterexample-driven refinement". SLAM exploits and extends results fi'om program analysis, model checking

Topological Simultaneous Localization and Mapping (SLAM): Toward Exact Localization Without Explicit Localization

by Howie Choset, Keiji Nagatani - IEEE Transactions on Robotics and Automation , 2001
"... One of the critical components of mapping an unknown environment is the robot's ability to locate itself on a partially explored map. This becomes challenging when the robot experiences positioning error, does not have an external positioning device, nor the luxury of engineered landmarks place ..."
Abstract - Cited by 224 (10 self) - Add to MetaCart
placed in its free space. This paper presents a new method for simultaneous localization and mapping that exploits the topology of the robot's free space to localize the robot on a partially constructed map. The topology of the environment is encoded in a topological map; the particular topological

Exploiting the Information at the Loop Closure in SLAM

by A. Martinelli, R. Siegwart , 2007
"... This paper presents two methods able to exploit the information at the loop closure in the SLAM problem. Both methods have three fundamental advantages. The first one is that to apply the loop closure constraint they do not require to compute any correlation among the features which are not observ ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
This paper presents two methods able to exploit the information at the loop closure in the SLAM problem. Both methods have three fundamental advantages. The first one is that to apply the loop closure constraint they do not require to compute any correlation among the features which

Improving the agility of keyframe-based SLAM

by Georg Klein, David Murray - In Proceedings of the European Conference on Computer Vision (ECCV , 2008
"... Abstract. The ability to localise a camera moving in a previously unknown environment is desirable for a wide range of applications. In computer vision this problem is studied as monocular SLAM. Recent years have seen improvements to the usability and scalability of monocular SLAM systems to the poi ..."
Abstract - Cited by 88 (2 self) - Add to MetaCart
approaches to improving the agility of a keyframe-based SLAM system: Firstly, we add edge features to the map and exploit their resilience to motion blur to improve tracking under fast motion. Secondly, we implement a very simple inter-frame rotation estimator to aid tracking when the camera is rapidly

Vision SLAM in the measurement subspace

by John Folkesson, Patric Jensfelt, Henrik I. Christensen - In Proc. of the IEEE International Conference on Robotics and Automation (ICRA , 2005
"... Abstract — In this paper we describe an approach to feature representation for simultaneous localization and mapping, SLAM. It is a general representation for features that addresses symmetries and constraints in the feature coordinates. Furthermore, the representation allows for the features to be ..."
Abstract - Cited by 43 (14 self) - Add to MetaCart
as the special properties of each type of feature are accounted for, the commonalities of all map features are also exploited to allow SLAM algorithms to be interchanged as well as choice of sensors and features. In other words the SLAM implementation need not be changed at all when changing sensors and features

Visually navigating the RMS Titanic with SLAM information filters

by Ryan Eustice, Hanumant Singh, Woods Hole, Woods Hole - in Proceedings of Robotics: Science and Systems , 2005
"... Abstract — This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We prese ..."
Abstract - Cited by 75 (12 self) - Add to MetaCart
Abstract — This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We

BS-SLAM: Shaping the World

by Luis Pedraza, Gamini Dissanayake, Jaime Valls Miro, Diego Rodriguez-losada, O Matia
"... Abstract — This paper presents BS-SLAM, a simultaneous localization and mapping algorithm for use in unstructured environments that is effective regardless of whether features correspond to simple geometric primitives such as lines or not. The coordinates of the control points defining a set of B-sp ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
Abstract — This paper presents BS-SLAM, a simultaneous localization and mapping algorithm for use in unstructured environments that is effective regardless of whether features correspond to simple geometric primitives such as lines or not. The coordinates of the control points defining a set of B

Using covariance intersection for SLAM

by Simon J. Julier A, Jeffrey K. Uhlmann B , 2006
"... www.elsevier.com/locate/robot One of the greatest obstacles to the use of Simultaneous Localization And Mapping (SLAM) in a real-world environment is the need to maintain the full correlation structure between the vehicle and all of the landmark estimates. This structure is computationally expensive ..."
Abstract - Add to MetaCart
www.elsevier.com/locate/robot One of the greatest obstacles to the use of Simultaneous Localization And Mapping (SLAM) in a real-world environment is the need to maintain the full correlation structure between the vehicle and all of the landmark estimates. This structure is computationally

A Tutorial on Graph-Based SLAM

by Giorgio Grisetti, Rainer Kümmerle, Cyrill Stachniss, Wolfram Burgard , 2010
"... Being able to build a map of the environment and to simultaneously localize within this map is an essential skill for mobile robots navigating in unknown environments in absence of external referencing systems such as GPS. This so-called simultaneous localization and mapping (SLAM) problem has been ..."
Abstract - Cited by 28 (4 self) - Add to MetaCart
with the measurements modeled by the edges. In this paper, we provide an introductory description to the graph-based SLAM problem. Furthermore, we discuss a state-of-the-art solution that is based on least-squares error minimization and exploits the structure of the SLAM problems during optimization. The goal

Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM

by Roshan Shariff, András György, Csaba Szepesvári
"... The Metropolis-Hastings (MH) algorithm is a flexible method to generate samples from a target distribution, a key problem in probabilistic infer-ence. In this paper we propose a variation of the MH algorithm based on group moves, where the next state is obtained by first choosing a random transforma ..."
Abstract - Add to MetaCart
extends the acceptance probability formula of the textbook algorithm to MH algorithms with group moves. We work out how the new algorithms can be used to exploit a problem’s natural symmetries and apply the technique to the simultaneous localization and mapping (SLAM) problem, obtaining the first fully
Next 10 →
Results 1 - 10 of 119
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University