Example of IEEE Transactions on Robotics format
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Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format
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Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format Example of IEEE Transactions on Robotics format
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IEEE Transactions on Robotics — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Control and Systems Engineering #5 of 260 up up by 5 ranks
Computer Science Applications #13 of 693 up up by 6 ranks
Electrical and Electronic Engineering #16 of 693 up up by 15 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 451 Published Papers | 7488 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 16/07/2020
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Related Journals

open access Open Access

IEEE

Quality:  
High
CiteRatio: 7.7
SJR: 0.864
SNIP: 1.736
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 17.7
SJR: 2.496
SNIP: 3.497
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 7.2
SJR: 1.175
SNIP: 1.687
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 7.3
SJR: 0.94
SNIP: 1.844

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

6.123

6% from 2018

Impact factor for IEEE Transactions on Robotics from 2016 - 2019
Year Value
2019 6.123
2018 6.483
2017 4.264
2016 4.036
graph view Graph view
table view Table view

16.6

17% from 2019

CiteRatio for IEEE Transactions on Robotics from 2016 - 2020
Year Value
2020 16.6
2019 14.2
2018 12.7
2017 9.4
2016 8.9
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 6% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 17% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

2.027

28% from 2019

SJR for IEEE Transactions on Robotics from 2016 - 2020
Year Value
2020 2.027
2019 2.815
2018 1.987
2017 1.822
2016 1.7
graph view Graph view
table view Table view

4.204

4% from 2019

SNIP for IEEE Transactions on Robotics from 2016 - 2020
Year Value
2020 4.204
2019 4.387
2018 4.161
2017 3.241
2016 2.512
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 28% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 4% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

IEEE Transactions on Robotics

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IEEE

IEEE Transactions on Robotics

IEEE Transactions on Robotics covers both theory and applications on topics including: kinematics, dynamics, control, and simulation of robots and intelligent machines and systems; design of robotic mechanisms; man-machine interface and integration; motion and manipulation; ro...... Read More

Engineering

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Last updated on
16 Jul 2020
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ISSN
1552-3098
i
Impact Factor
Very High - 3.891
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
IEEEtran
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Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1109/TRO.2015.2463671
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
Raul Mur-Artal1, J. M. M. Montiel1, Juan D. Tardós1

Abstract:

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 initializa... 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 from scratch a novel system that uses the same features for all SLAM tasks: tracking, mapping, relocalization, and loop closing. 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. We present an exhaustive evaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves unprecedented performance with respect to other state-of-the-art monocular SLAM approaches. For the benefit of the community, we make the source code public. read more read less

Topics:

Simultaneous localization and mapping (53%)53% related to the paper
View PDF
4,522 Citations
open accessOpen access Journal Article DOI: 10.1109/TRO.2017.2705103
ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
Raul Mur-Artal1, Juan D. Tardós1

Abstract:

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 seq... 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 driving around a city. Our back-end, based on bundle adjustment with monocular and stereo observations, allows for accurate trajectory estimation with metric scale. Our system includes a lightweight localization mode that leverages visual odometry tracks for unmapped regions and matches with map points that allow for zero-drift localization. The evaluation on 29 popular public sequences shows that our method achieves state-of-the-art accuracy, being in most cases the most accurate SLAM solution. We publish the source code, not only for the benefit of the SLAM community, but with the aim of being an out-of-the-box SLAM solution for researchers in other fields. read more read less

Topics:

Simultaneous localization and mapping (56%)56% related to the paper, Visual odometry (54%)54% related to the paper, Bundle adjustment (50%)50% related to the paper
3,499 Citations
open accessOpen access Journal Article DOI: 10.1109/TRO.2018.2853729
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Tong Qin1, Peiliang Li1, Shaojie Shen1

Abstract:

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 es... 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 for estimator initialization. A tightly coupled, nonlinear optimization-based method is used to obtain highly accurate visual-inertial odometry by fusing preintegrated IMU measurements and feature observations. A loop detection module, in combination with our tightly coupled formulation, enables relocalization with minimum computation. We additionally perform 4-DOF pose graph optimization to enforce the global consistency. Furthermore, the proposed system can reuse a map by saving and loading it in an efficient way. The current and previous maps can be merged together by the global pose graph optimization. We validate the performance of our system on public datasets and real-world experiments and compare against other state-of-the-art algorithms. We also perform an onboard closed-loop autonomous flight on the microaerial-vehicle platform and port the algorithm to an iOS-based demonstration. We highlight that the proposed work is a reliable, complete, and versatile system that is applicable for different applications that require high accuracy in localization. We open source our implementations for both PCs ( https://github.com/HKUST-Aerial-Robotics/VINS-Mono ) and iOS mobile devices ( https://github.com/HKUST-Aerial-Robotics/VINS-Mobile ). read more read less

Topics:

Odometry (52%)52% related to the paper, Inertial measurement unit (51%)51% related to the paper, Initialization (50%)50% related to the paper, Estimator (50%)50% related to the paper
2,305 Citations
open accessOpen access Journal Article DOI: 10.1109/TRO.2006.889486
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
Giorgio Grisetti1, Cyrill Stachniss1, Wolfram Burgard1

Abstract:

Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous localization and mapping problem. This approach uses a particle filter in which each particle carries an individual map of the environment. Accordingly, a key question is how to reduce the number of particl... Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous localization and mapping problem. This approach uses a particle filter in which each particle carries an individual map of the environment. Accordingly, a key question is how to reduce the number of particles. In this paper, we present adaptive techniques for reducing this number in a RBPF for learning grid maps. We propose an approach to compute an accurate proposal distribution, taking into account not only the movement of the robot, but also the most recent observation. This drastically decreases the uncertainty about the robot's pose in the prediction step of the filter. Furthermore, we present an approach to selectively carry out resampling operations, which seriously reduces the problem of particle depletion. Experimental results carried out with real mobile robots in large-scale indoor, as well as outdoor, environments illustrate the advantages of our methods over previous approaches read more read less

Topics:

Monte Carlo localization (64%)64% related to the paper, Simultaneous localization and mapping (63%)63% related to the paper, Particle filter (57%)57% related to the paper, Mobile robot (53%)53% related to the paper, Filter (signal processing) (51%)51% related to the paper
View PDF
2,209 Citations
open accessOpen access Journal Article DOI: 10.1109/TRO.2016.2624754
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
Cesar Cadena1, Luca Carlone2, Henry Carrillo3, Yasir Latif4, Davide Scaramuzza5, José Neira6, Ian Reid4, John J. Leonard2

Abstract:

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 st... 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 industry. We survey the current state of SLAM and consider future directions. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors’ take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved? read more read less

Topics:

Simultaneous localization and mapping (51%)51% related to the paper
View PDF
2,039 Citations
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IEEE Transactions on Robotics format uses IEEEtran citation style.

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Frequently asked questions

1. Can I write IEEE Transactions on Robotics in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IEEE Transactions on Robotics guidelines and auto format it.

2. Do you follow the IEEE Transactions on Robotics guidelines?

Yes, the template is compliant with the IEEE Transactions on Robotics guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IEEE Transactions on Robotics?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IEEE Transactions on Robotics citation style.

4. Can I use the IEEE Transactions on Robotics templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IEEE Transactions on Robotics.

5. Can I use a manuscript in IEEE Transactions on Robotics that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IEEE Transactions on Robotics that you can download at the end.

6. How long does it usually take you to format my papers in IEEE Transactions on Robotics?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IEEE Transactions on Robotics.

7. Where can I find the template for the IEEE Transactions on Robotics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Robotics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IEEE Transactions on Robotics's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IEEE Transactions on Robotics an online tool or is there a desktop version?

SciSpace's IEEE Transactions on Robotics is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like IEEE Transactions on Robotics?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like IEEE Transactions on Robotics?”

11. What is the output that I would get after using IEEE Transactions on Robotics?

After writing your paper autoformatting in IEEE Transactions on Robotics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IEEE Transactions on Robotics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IEEE Transactions on Robotics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IEEE Transactions on Robotics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IEEE Transactions on Robotics?

The 5 most common citation types in order of usage for IEEE Transactions on Robotics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IEEE Transactions on Robotics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Robotics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IEEE Transactions on Robotics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IEEE Transactions on Robotics Endnote style according to Elsevier guidelines.

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