scipy-conference / scipy_proceedings_2012

2012 SciPy conference proceedings
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Review of "Self-driving Lego Mindstorms Robot" #12

Open moorepants opened 10 years ago

moorepants commented 10 years ago

Independent Review Report

.. note:: Please be aware that all reviews are made public including the reviewer's name.

Reviewer: Jason K. Moore

Department/Center/Division: Human Motion and Control Lab, Mechanical Engineering Department

Institution/University/Company: Cleveland State University

Field of interest / expertise: multibody dynamics, biomechanics, control systems, system identification

Country: USA

Article reviewed: Self-driving Lego Mindstorms Robot

INSTRUCTIONS

Please read the submitted article and fully complete this form. Since we don't have a copy editor, we also request that you annotate the PDF [1]_ to highlight typos, formatting issues, and grammatical mistakes.

The goal of the review process is two-fold. First, it guides authors in improving their papers and, secondly, ensures that published works are of a professional academic standard.

Research in science and engineering increasingly relies on software for data processing and management as well as theoretical exploration. However, the effort necessary to develop this software is rarely recognized as having the same academic worth as other aspects of the research. These proceedings are, at least in part, intended to address this shortcoming.

An article focused on software development necessarily differs from the standard scientific article with respect to format. For instance, it is unlikely to have the same sections (i.e., introduction, methods, results, conclusion). You may therefore have to rely on other factors to decide whether the paper sets a high enough standards as an academic publication.

Please note that, while reviewers' recommendations regarding a paper's suitability for publication are seriously considered, the final decision rests with the proceeding editors.

.. [1] We recommend the free version of PDF XChange Viewer <http://www.tracker-software.com/product/pdf-xchange-viewer> for Linux (Wine) and Windows. Under OSX, annotation is provided by Preview as well as Skim <http://skim-app.sourceforge.net/>.

GENERAL EVALUATION

Please rate the paper using the following criteria (please use the abbreviation to the right of the description)::

below doesn't meet standards for academic publication meets meets or exceeds the standards for academic publication n/a not applicable

For the following questions, please respond with 'yes' or 'no'. If you answer 'no', please provide a brief, one- to two-sentence explanation.

Yes, the code is publicly available and relies on a variety of open source packages. The software can be downloaded from the github link provided in the paper. The Android image capture library may not be open source.

Yes.

Specifically, does it:

Yes, he gives background on self-driving car research to show the need.

Maybe, only a couple of papers are cited about self-driving vehicles and techniques. Much of the literature is not present and no detailed commentary on how the method presented in the paper compares to other approaches.

Yes, the paper seems to be written with a non-expert audience in mind.

Yes.

No, the paper doesn't propose a hypothesis or follow the scientific method. It is more like a report on how to use several software libraries to accomplish a task rather than a well-formulated scientific achievement. I guess it can be called a "technical achievement" because the author achieved his goal of reproducing another's work with different software and hardware.

No, the motivation only seems to be to replicate previous work. The reasons for choosing the hardware, software, and parameters for both are not explained at all. It seems as if the author just used informed guesses at values for the neural network, for example.

Yes, but it'd be nice if they followed PEP8 standards for readability reasons.

Yes, the method and results seem to be factually correct.

Yes.

No, because there are no conclusions. The paper simply describes how something is done. Most scientific works explain what the conclusions are and make some reasoning on why those conclusions are true. The conclusion here seems to be simply that someone else's work can be replicated with different hardware and software while using the same methods.

No. The blog post that described the work that is being replicated is cited with a URL and a few academic papers are cited, but the wide berth of work on self-driving vehicles and neural networks has been ignored.

Yes. The prior literature on the subject should be expanded and comparisons in this method and others is needed. Furthermore, there should be some scientific discourse on the details of this method along with quantitative measures describing the performance of this technique so that comparisons can be made to other software, hardware, and methods.

This paper presents the replication of a "self-driving" robot vehicle implementation that utilizes a trained neural network to follow a specific course using visual inputs to control the vehicle's driving motors. From what is written, it seems that using a Python based software stack and the Lego robot kit, that prior work can be replicated. But the article does not exhibit the depth that other quality scientific articles on this subject offer. The reader is simply instructed in the how, i.e. the method, of implementing this system using a very specific selection of software packages. Little to no information is provided that gives the reader technical information on the capabilities of this method, particularly not for comparison purposes to other methods. No hypothesis or claim is made nor any proof to back it up the missing claim. The article seems more akin to a undergraduate lab tutorial that simply shows the student how to do something, but misses the "why" portion that generally makes a contribution interesting and publishable for the scientific community. I think this article could be transformed into a valuable scientific contribution if these things were changed/added:

  1. A proper literature review on other methods. At the minimum, this could detail other software libraries with these capabilities and at the maximum this could include comparison to other methods of autonomously controlling a vehicle.
  2. A statement, hypothesis, or claim about what makes this method special/difference and the proof to back it up. If this is simply a replication study of previous work using different methods, then the claims from the previous study should also be proved by the method presented in this paper along with detailed quantitative comparisons of how well the other method was replicated.
  3. More technical detail on the method. If comparing software, we need to know things like how easy it is to use, how fast it is, how robust it is, what are the limitations, etc all with respect to other available software. The technical details of the hardware are also important so that we no its advantages and limitations with respect to other methods. If comparing algorithms (neural nets, etc) then we need to know more detail about the methods and why the parameters you chose are good and what they mean. Explanation of the neural net framework you chose and why would be helpful.
  4. Give accurate and precise results. Simply saying that your vehicle completes the course "about 2/3rds" of the time is not science. You also need dimensional descriptions of the course, the vehicle, and metrics on how bad or good it actually performs. No one can compare their vehicle and implementation to yours if this isn't provided. We also have no idea if you actually replicated the prior work because there are no quantitative measures.
  5. The tone and grammar of the paper resembles a blog post as opposed to a scientific article. I'm not opposed to having more personal writing, but it needs to be justified and it needs to contribute to the understanding of the article. As it stands, this would be a fine blog post but it is quite far from an average scientific article.