ORB-SLAM: A Versatile and Accurate Monocular SLAM System
- Raul Mur-Artal, J. Montiel, J. D. Tardós
- Computer ScienceIEEE Transactions on robotics
- 3 February 2015
A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation.
ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
- Raul Mur-Artal, J. D. Tardós
- Computer ScienceIEEE Transactions on robotics
- 20 October 2016
ORB-SLAM2, a complete simultaneous localization and mapping (SLAM) system for monocular, stereo and RGB-D cameras, including map reuse, loop closing, and relocalization capabilities, is presented, being in most cases the most accurate SLAM solution.
Bags of Binary Words for Fast Place Recognition in Image Sequences
- Dorian Gálvez-López, J. D. Tardós
- Computer ScienceIEEE Transactions on robotics
- 1 October 2012
A vocabulary tree is built that discretizes a binary descriptor space and uses the tree to speed up correspondences for geometrical verification, and presents competitive results with no false positives in very different datasets.
Data association in stochastic mapping using the joint compatibility test
- José Neira, J. D. Tardós
- MathematicsIEEE Trans. Robotics Autom.
- 1 December 2001
This paper proposes a new measurement of the joint compatibility of a set of pairings that successfully rejects spurious matchings and shows experimentally that this restrictive criterion can be used to efficiently search for the best solution to data association.
Visual-Inertial Monocular SLAM With Map Reuse
- Raul Mur-Artal, J. D. Tardós
- Computer ScienceIEEE Robotics and Automation Letters
- 19 October 2016
This letter presents a novel tightly coupled visual-inertial simultaneous localization and mapping system that is able to close loops and reuse its map to achieve zero-drift localization in already mapped areas.
Robust Mapping and Localization in Indoor Environments Using Sonar Data
- J. D. Tardós, José Neira, P. Newman, J. Leonard
- Computer ScienceInt. J. Robotics Res.
- 1 April 2002
A perceptual grouping process that permits the robust identification and localization of environmental features from the sparse and noisy sonar data, and a map joining technique that allows the system to build a sequence of independent limited-size stochastic maps and join them in a globally consistent way.
Hierarchical SLAM: real-time accurate mapping of large environments
- Carlos Estrada, José Neira, J. D. Tardós
- Computer ScienceIEEE Transactions on robotics
- 1 August 2005
A close to optimal loop closing method is proposed that, while maintaining independence at the local level, imposes consistency at the global level at a computational cost that is linear with the size of the loop.
Mapping Large Loops with a Single Hand-Held Camera
- Laura A. Clemente, A. Davison, I. Reid, José Neira, J. D. Tardós
- EngineeringRobotics: Science and Systems
- 27 June 2007
This paper presents a method for Simultaneous Localization and Mapping (SLAM) relying on a monocular camera as the only sensor which is able to build outdoor, closedloop maps much larger than…
Mobile Robot Localization and Map Building: A Multisensor Fusion Approach
- J. A. Castellanos, J. D. Tardós
- Computer Science
- 31 March 2000
A new probabilistic framework adapted to the problem of simultaneous localization and map building for mobile robots is proposed: the Symmetries and Perturbations Map (SPmap).
Robocentric map joining: Improving the consistency of EKF-SLAM
- J. A. Castellanos, Ruben Martinez-Cantin, J. D. Tardós, José Neira
- MathematicsRobotics Auton. Syst.
- 1 January 2007
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