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IEEE Transactions on Robotics is a peer-reviewed journal published by IEEE, covering Robot Manipulation and Learning, Robotic Path Planning Algorithms, Soft Robotics and Applications. Over its lifetime it has published 4,181 papers, which have received 274,950 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Robotics, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Robotics style. No sign-up. |
| Abbreviation (ISO-4) | TRO |
| Publishes research in | Robot Manipulation and Learning Robotic Path Planning Algorithms Soft Robotics and Applications Robotics and Sensor-Based Localization Robotic Mechanisms and Dynamics |
| ISSN | 1552-3098 |
| Citation impact (2-yr) | 7.8 |
| h-index | 227 |
| i10-index | 2,691 |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
This paper presents ORB-SLAM, a feature-based monocular simultaneous localization and mapping (SLAM) system that operates in real time, in small and large indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization. Building on excellent algorithms of recent years, we designed…
We present 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. The system works in real time on standard central processing units in a wide variety of environments from small hand-held indoors sequences, to drones flying in industrial environments and cars…
One camera and one low-cost inertial measurement unit (IMU) form a monocular visual-inertial system (VINS), which is the minimum sensor suite (in size, weight, and power) for the metric six degrees-of-freedom (DOF) state estimation. In this paper, we present VINS-Mono: a robust and versatile monocular visual-inertial state estimator. Our approach starts with a robust procedure…
This article presents ORB-SLAM3, the first system able to perform visual, visual-inertial and multimap SLAM with monocular, stereo and RGB-D cameras, using pin-hole and fisheye lens models. The first main novelty is a tightly integrated visual-inertial SLAM system that fully relies on maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> (MAP) estimation, even during IMU initialization, resulting in…
Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications and witnessing a steady transition of this technology to…
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