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I'm working under a professor as a research assistant. She is preparing a proposal for research she wants to do with unmanned vehicles. A part of this proposal is showing that the past research doesn't focus on large numbers of vehicles, and the ones that do are not as intelligent and use "swarm behavior". Her research will focus on large groups or intelligent vehicles, and wants to show that she is doing something that is rarely researched. She's tasked me with putting together a list of the past research in this field noting the number of vehicles each paper experimented with and whether it was low level swarm behavior or something more intelligent.

As I'm putting together this data, how can I show there's a hole in the current research without citing hundreds and hundreds of papers? Does what I'm doing have a name that I don't know about?

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    . . . and the ones that do are not as intelligent and use "swarm behavior" Do you mean rather: . . . and the ones that do are not as intelligent nor use "swarm behavior" ?
    – Trunk
    Jun 11 at 12:12

5 Answers 5

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As I'm putting together this data, how can I show there's a hole in the current research without citing hundreds and hundreds of papers?

You are being asked to cite hundreds and hundreds of papers (if that's how many there are).

Does what I'm doing have a name that I don't know about?

Depending on exactly what you are doing, this is most likely a "systematic review," or (less likely) a "meta-analysis."

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    If there is already a paper with a sufficient bibliography you could also point to it, rather than listing everything again.
    – Buffy
    Jun 10 at 18:25
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    As the OP does not indicate that statistical values (for example on UMV performance metrics) are relevant, I don't think a meta-analysis is of any use here. Also typically for proposals you don't do these analyses, you do a focused literature review.
    – jadepx
    Jun 11 at 16:28
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    @jadepx That's why I said "depending on exactly what you are doing." I meant to imply that it was more likely to be a "systematic review," but I wanted to include "meta-analysis" since it seems like OP is fairly new and that might help them locate resources. Jun 11 at 17:00
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It is not possible to enumerate all works. First, in the area of unmanned vehicles, there are upwards of 10K+ papers. Second, it is impossible to check whether you have covered all papers. Moreover, each day, there will be new papers posted online. Lastly, authors may call a concept by a non-standard name, which means you will miss their papers.

My strategy:

First, determine the key contributions that you wish to make. List all potential gaps or ideas you think are new.

Second, from your list, draw up a bunch of keywords, e.g., 'vehicles+platoon+swarm+intelligent'.

Third, search for these keywords, and read the Abstract of papers to determine whether they are closely related to your ideas. If there are too many keywords, you may not find any works. Then it is time to remove or change some keywords. Alternatively, you may find too many papers. Then it is time to add or change keywords.

Fourth, form a mind map of what the general research aims or setups of works in your area(s).

Fifth, write down identified gaps and how your work relates to prior works. This is where you will say 'To the best of our knowledge, ...'

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Although some other answers have suggested a comprehensive systematic review, I do not think that is feasible or even desirable for your purpose of providing evidence for novelty for a single project. Let me suggest a different strategy that might be more practical.

  1. You should search for articles on this topic published in the past two or three years. Presumably, such articles will have tried to do some kind of review to demonstrate their own novelty, so read these sections carefully to see if there are any articles that they have identified that are similar to what you are doing.
  2. Look up any articles referenced by the first round articles that seem relevant and then likewise carefully read their novelty sections to see if there is anything similar. Repeat this process iteratively until you are satisfied that you have found what is considered to be "new" in the relatively recent literature.
  3. The previous steps are a good start, but are not sufficient. So, next, among the most relevant articles that you have located (all of which have been published relatively recently), try to contact the authors of those articles and ask them directly by email if they have anything to recommend to you related to your topic. Recently published authors should be quite knowledgeable, so if they reply, they could quickly cut your work short for you. To increase chances of replying, I recommend that you email each author of each highly relevant article individually (not as a group). Hopefully, even if just a few reply, you should get some very valuable pointers.

Concerning the last step of contacting authors, be sure to get your professor to agree first, and to get her to preapprove the email that you send out--you do not want to divulge more details about your project than she is comfortable with.

One point to note about contacting authors is that when your article is eventually sent out for peer review, there is a good chance that some of those authors whom you have contacted might be selected as anonymous peer reviewers. This might or might not be a benefit. The positive side is that, if they respond, at least you wll be sure to include references that they include important.

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You must cover all the ground but you don't have to start at one end and chop your way laboriously through the forest of papers on this topic.

Your main task is to demonstrate that existing literature/conference proceedings on this topic do not really explore UMVs that are "highly intelligent" nor the behaviour of large collections of UMVs.

  1. You must do computerized literature searches that check past publication archives on UMVs for any papers having certain phrases like "intelligent", "very intelligent", "swarm", "swarm behavior", etc in the English abstract of the journal/proceedings.

Clearly, if you find a significant amount of work already done on this you will at least save yourself (and the professor) considerable additional effort and/or avoid duplicating research.

  1. You can, and should, make use of the existing review papers on UMVs from the commencement of research into it so as to expedite sourcing all the seminal and salient contributions. Give close attention to the papers cited on your topic in the review papers and then follow the trail of citations in each of these. You'll often find important review papers/presentations at major conferences for this topic. If no conferences exist that are wholly devoted to this, find the general heading for such research and locate the conferences embracing your area. It might also be wise to survey the more industrial conferences covering UMV applications for papers that might be published there. In the latter regard give especial attention to application areas where intelligent UMVs or UMV swarms could be very effective. (People may choose to publish here if they seek industrial support for an approach that is seen as less popular to the usual research council sponsors.)

Make sure you study every relevant paper cited in a review paper and note the paper details.

  1. Enumeration of major past UMV research should initially be done chronologically, I think. This will help you to comprehend the timeline evolution of this approach to the art from the beginning to its present state, the impact of supporting technologies and driving factors for the technology like the emergence of promising applications.

  2. About a quarter of the way along the chronology, start sketching out the purely technological evolution of UMVs as a sort of tree diagram where notable developments and associated researchers are briefly noted. This tree will likely have 'branches' that lead to:

  • Dead wood (ideas that proved unsuccessful);

  • Sudden thinning out to nothing (e.g. researcher changes research topic / gets new university not interested in old topic / dies young, all without assumption of his past work by others);

  • Branch thickening as a new idea produces interesting results and thus more activity by others;

  • Re-branching as an active research objective offers alternate approaches, etc.

That much should be adequate to help your professor decide if there's a point in pursuing your professor's angle on UMVs.

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You might want to start by testing whether the hypothesis is correct. Try and actively look for papers that are similar to the proposed work.

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