Example of Frontiers in Robotics and AI format
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open access Open Access

Frontiers in Robotics and AI — Template for authors

Publisher: Frontiers Media
Categories Rank Trend in last 3 yrs
Computer Science Applications #202 of 693 down down by 39 ranks
Artificial Intelligence #90 of 227 down down by 24 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 473 Published Papers | 2062 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 26/06/2020
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Related Journals

open access Open Access

Hindawi

Quality:  
High
CiteRatio: 5.0
SJR: 0.371
SNIP: 1.169
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recommended Recommended

IEEE

Quality:  
High
CiteRatio: 19.8
SJR: 2.882
SNIP: 3.86
open access Open Access
recommended Recommended

American Association for the Advancement of Science

Quality:  
High
CiteRatio: 25.7
SJR: 5.619
SNIP: 5.246

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

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

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.

4.4

6% from 2019

CiteRatio for Frontiers in Robotics and AI from 2016 - 2020
Year Value
2020 4.4
2019 4.7
2018 3.1
2017 3.7
graph view Graph view
table view Table view

0.547

19% from 2019

SJR for Frontiers in Robotics and AI from 2018 - 2020
Year Value
2020 0.547
2019 0.675
2018 0.527
graph view Graph view
table view Table view

1.622

16% from 2019

SNIP for Frontiers in Robotics and AI from 2017 - 2020
Year Value
2020 1.622
2019 1.404
2018 1.56
2017 1.479
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has decreased by 6% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 19% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 16% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Frontiers in Robotics and AI

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Frontiers Media

Frontiers in Robotics and AI

Approved by publishing and review experts on SciSpace, this template is built as per for Frontiers in Robotics and AI formatting guidelines as mentioned in Frontiers Media author instructions. The current version was created on 26 Jun 2020 and has been used by 146 authors to write and format their manuscripts to this journal.

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Last updated on
26 Jun 2020
i
Open Access
No
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Sherpa RoMEO Archiving Policy
Green faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
frontiersinSCNS_ENG_HUMS
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder GE, Tinkham M, Klapwijk TM. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B 25 (1982) 4515–4532.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.3389/FROBT.2016.00040
Quality Diversity: A New Frontier for Evolutionary Computation
Justin K. Pugh1, L. B. Soros1, Kenneth O. Stanley1

Abstract:

While evolutionary computation and evolutionary robotics take inspiration from nature, they have long focused mainly on problems of performance optimization. Yet evolution in nature can be interpreted as more nuanced than a process of simple optimization. In particular, natural evolution is a divergent search that optimizes l... While evolutionary computation and evolutionary robotics take inspiration from nature, they have long focused mainly on problems of performance optimization. Yet evolution in nature can be interpreted as more nuanced than a process of simple optimization. In particular, natural evolution is a divergent search that optimizes locally within each niche as it simultaneously diversifies. This tendency to discover both quality and diversity at the same time differs from many of the conventional algorithms of machine learning, and also thereby suggests a different foundation for inferring the approach of greatest potential for evolutionary algorithms. In fact, several recent evolutionary algorithms called quality diversity (QD) algorithms(e.g. novelty search with local competition and MAP-Elites) have drawn inspiration from this more nuanced view, aiming to fill a space of possibilities with the best possible example of each type of achievable behavior. The result is a new class of algorithms that return an archive of diverse, high-quality behaviors in a single run. The aim in this paper is to study the application of QD algorithms in challenging environments (in particular complex mazes) to establish their best practices for ambitious domains in the future. In addition to providing insight into cases when QD succeeds and fails, a new approach is investigated that hybridizes multiple views of behaviors (called behavior characterizations) in the same run, which succeeds in overcoming some of the challenges associated with searching for QD with respect to a behavior characterization that is not necessarily sufficient for generating both quality and diversity at the same time. read more read less

Topics:

Evolutionary computation (61%)61% related to the paper, Evolutionary robotics (58%)58% related to the paper, Evolutionary algorithm (57%)57% related to the paper, Neuroevolution (56%)56% related to the paper
View PDF
466 Citations
open accessOpen access Journal Article DOI: 10.3389/FROBT.2015.00028
A Review of Human Activity Recognition Methods
Michalis Vrigkas1, Christophoros Nikou1, Ioannis A. Kakadiaris2

Abstract:

Recognizing human activities from video sequences or still images is a challenging task due to problems such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance. Many applications, including video surveillance systems, human-computer interaction, and robotics for human behavior char... Recognizing human activities from video sequences or still images is a challenging task due to problems such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance. Many applications, including video surveillance systems, human-computer interaction, and robotics for human behavior characterization, require a multiple activity recognition system. In this work, we provide a detailed review of recent and state-of-the-art research advances in the field of human activity classification. We propose a categorization of human activity methodologies and discuss their advantages and limitations. In particular, we divide human activity classification methods into two large categories according to whether they use data from different modalities or not. Then, each of these categories is further analyzed into sub-categories, which reflect how they model human activities and what type of activities they are interested in. Moreover, we provide a comprehensive analysis of the existing, publicly available human activity classification datasets and examine the requirements for an ideal human activity recognition dataset. Finally, we report the characteristics of future research directions and present some open issues on human activity recognition. read more read less

Topics:

Activity recognition (55%)55% related to the paper
View PDF
395 Citations
open accessOpen access Journal Article DOI: 10.3389/FROBT.2016.00069
Soft manipulators and grippers: A review
Josie Hughes1, Utku Culha2, Fabio Giardina1, Fabian Guenther2, Andre Rosendo1, Fumiya Iida1

Abstract:

Soft robotics is a growing area of research which utilises the compliance and adaptability of soft structures to develop highly adaptive robotics for soft interactions. One area in which soft robotics has the ability to make significant impact is in the development of soft grippers and manipulators. With an increased requirem... Soft robotics is a growing area of research which utilises the compliance and adaptability of soft structures to develop highly adaptive robotics for soft interactions. One area in which soft robotics has the ability to make significant impact is in the development of soft grippers and manipulators. With an increased requirement for automation, robotics systems are required to perform task in unstructured and not well defined environments; conditions which conventional rigid robotics are not best suited. This requires a paradigm shift in the methods and materials used to develop robots such that they can adapt to and work safely in human environments. One solution to this is soft robotics, which enables soft interactions with the surroundings whilst maintaining the ability to apply significant force. This review paper assess the current materials and methods, actuation methods and sensors which are used in the development of soft manipulators. The achievements and shortcomings of recent technology in these key areas are evaluated, and this paper concludes with a discussion on the potential impacts of soft manipulators on industry and society. read more read less

Topics:

Soft robotics (75%)75% related to the paper, Robot (55%)55% related to the paper, Robotics (55%)55% related to the paper, Grippers (52%)52% related to the paper
View PDF
388 Citations
open accessOpen access Journal Article DOI: 10.3389/FROBT.2016.00003
Real Virtuality: A Code of Ethical Conduct. Recommendations for Good Scientific Practice and the Consumers of VR-Technology
Michael Madary1, Thomas Metzinger1

Abstract:

The goal of this article is to present a first list of ethical concerns that may arise from research and personal use of virtual reality (VR) and related technology, and to offer concrete recommendations for minimizing those risks. Many of the recommendations call for focused research initiatives. In the first part of the art... The goal of this article is to present a first list of ethical concerns that may arise from research and personal use of virtual reality (VR) and related technology, and to offer concrete recommendations for minimizing those risks. Many of the recommendations call for focused research initiatives. In the first part of the article, we discuss the relevant evidence from psychology that motivates our concerns. In section 1.1, we cover some of the main results suggesting that one’s environment can influence one’s psychological states, as well as recent work on inducing illusions of embodiment. Then, in section 1.2, we go on to discuss recent evidence indicating that immersion in VR can have psychological effects that last after leaving the virtual environment. In the second part of the article we turn to the risks and recommendations. We begin, in section 2.1, with the research ethics of VR, covering six main topics: the limits of experimental environments, informed consent, clinical risks, dual-use, online research, and a general point about the limitations of a code of conduct for research. Then, in section 2.2, we turn to the risks of VR for the general public, covering four main topics: long-term immersion, neglect of the social and physical environment, risky content, and privacy. We offer concrete recommendations for each of these ten topics, summarized in Table 1. read more read less

Topics:

Research ethics (54%)54% related to the paper, Immersive technology (54%)54% related to the paper, Ethical code (52%)52% related to the paper, Online research methods (51%)51% related to the paper
View PDF
262 Citations
open accessOpen access Journal Article DOI: 10.3389/FROBT.2015.00004
Evolutionary Robotics: What, Why, and Where to

Abstract:

Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the wh... Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the whole robot at once, and enables the exploitation of robot features in a holistic manner. Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. The use of robots as a substrate can help address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. In this paper we consider the main achievements of evolutionary robotics, focusing particularly on its contributions to both engineering and biology. We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work. read more read less

Topics:

Developmental robotics (66%)66% related to the paper, Evolutionary robotics (65%)65% related to the paper, Cognitive robotics (61%)61% related to the paper, Robotic paradigms (60%)60% related to the paper, Robot (58%)58% related to the paper
View PDF
218 Citations
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Frequently asked questions

1. Can I write Frontiers in Robotics and AI in LaTeX?

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

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Yes, the template is compliant with the Frontiers in Robotics and AI 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 Frontiers in Robotics and AI?

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 Frontiers in Robotics and AI citation style.

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5. Can I use a manuscript in Frontiers in Robotics and AI 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 Frontiers in Robotics and AI that you can download at the end.

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SciSpace's Frontiers in Robotics and AI 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.

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12. Is Frontiers in Robotics and AI'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 Frontiers in Robotics and AI?

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 Frontiers in Robotics and AI. 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 Frontiers in Robotics and AI?

The 5 most common citation types in order of usage for Frontiers in Robotics and AI 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 Frontiers in Robotics and AI?

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 Frontiers in Robotics and AI's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Frontiers in Robotics and AI 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 Frontiers in Robotics and AI Endnote style according to Elsevier guidelines.

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