CovPlan

[sanjeevrs2000]

Submitting Author: Name (@sanjeevrs2000)
All current maintainers: (@sanjeevrs2000)
Package Name: CovPlan
One-Line Description of Package: A Python package that generates guidance trajectories for field coverage using a single robot.
Repository Link: https://github.com/sanjeevrs2000/covplan
Version submitted: 0.1.0
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Description

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  This Python package generates a guidance trajectory for complete coverage in 2 dimensions. It can be used for operations where complete coverage of an Area of Interest (AoI) is required for applications in field robotics. If the area of interest is large or if it has any forbidden regions or obstacles, it could be divided into smaller sections and covered sequentially where the sequence is optimized using a travelling salesman problem (TSP) solver to minimize the overall distance. It also uses Dubins curves to generate continuous and feasible trajectories.

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It can be classified under applications in AI and robotics. Unsure which of the above categories it comes under but were encouraged to make a submission in the presubmission enquiry. Researchers in coverage path planning might find it useful for developing new algorithms or comparing it against their own methods. It has potential applications in field robotics where coverage of an area is required for monitoring, information gathering tasks.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?
  Fields2Cover is a similar implementation although it is in C++. Our work also considers more complex areas for coverage such as ones with forbidden regions and solves it by using a divide and conquer approach. It is also not limited to agriculture related applications and can be adapted for other uses by modifying the parameters

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[isabelizimm]

Welcome to pyOpenSci--we are so glad you are here! Thank you for this submission, just letting you know we have seen this issue and will get back to you with pre-review checks shortly. 🌻

[Gonzalo-Mier]

Hi @sanjeevrs2000, the CovPlan seems a cool repo.

I've found the mention to the Fields2Cover project and I would add some info to your claim:

Fields2Cover is a similar implementation although it is in C++.

Fields2Cover provides is implemented in C++, and provides a Python interface using swig

Our work also considers more complex areas for coverage such as ones with forbidden regions and solves it by using a divide and conquer approach.

This has been included in fields2cover v2 (released this week).

It is also not limited to agriculture related applications and can be adapted for other uses by modifying the parameters

Same as Fields2Cover. The focus is agriculture, but it is not limited.

Other Python package that implement coverage path planners: https://github.com/RuslanAgishev/motion_planning

Btw, congrats for the @pyOpenSci project to their authors!

[sanjeevrs2000]

Hi @Gonzalo-Mier, thanks a lot for the info. We were not aware of these recent developments with Fields2Cover. Keep up the great work with your repo!

[Batalex]

Hello @sanjeevrs2000,
Thank you for your patience. You may not know, but we now implement a 3-month rotation for the editor-in-chief role. I'll get started with the EiC checks right now.

[Batalex]

Hi @Gonzalo-Mier, welcome to pyOpenSci!

Thanks for the info. As @NickleDave reminded me, Fields2Cover was mentioned in the presubmission inquiry a few months ago.
As we already decided that CovPlan was in scope, we most likely will proceed with the review.

Now for the shameless part 😁
Though we do try to avoid duplication of efforts (hence our question on similar packages), we do not position ourselves as an authority on which package should be the reference. If anything, I would love for this GH issue to be the starting point of a collaborative effort that would benefit everyone.
If you are interested and available, please let me know!

[Batalex]

Editor in Chief checks

Hi there! Thank you for submitting your package for pyOpenSci review. Below are the basic checks that your package needs to pass to begin our review. If some of these are missing, we will ask you to work on them before the review process begins.

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  • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
    ✨ Please add some docstrings to document user-facing functions.
• Core GitHub repository Files
  • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
    ✨ I think we could use some more structure in the readme. "Getting started" should be like a 30 sec tutorial, not the description and even less the reference paper. See below for a suggestion
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  ✨ No tests at the moment
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Editor comments

As of now, there are too many missing things to get started with the review. Some are really trivial (like adding a CONTRIBUTING.md or restructuring the readme using the suggestion below), others require additional work.

I encourage you to go through our Python Package Guide to get familiar with:

• Python docstrings, and why you should use them to document your code
• Unit testing to avoid regressions in your code
• How to structure your package files

README.md suggested structure

Expand

# CovPlan

A Python package for coverage path planning.


[![MIT License](https://img.shields.io/badge/License-MIT-green.svg)](https://choosealicense.com/licenses/mit/)


A brief description of what this project does and who it's for. 

Link to paper + full citation

> Hameed IA, Bochtis D, Sørensen CA. An Optimized Field Coverage Planning Approach for Navigation of Agricultural Robots in Fields Involving Obstacle Areas. International Journal of Advanced Robotic Systems. 2013;10(5). doi:10.5772/56248

## Installation

Install `covplan` with pip

```shell
pip install covplan
```
    
## Getting started

The 30 seconds tutorial.

```py
import antigravity
```

## Documentation

[Documentation](https://linktodocumentation)

## Contributing

Contributions are always welcome!

See `contributing.md` for ways to get started.

Please adhere to this project's `code of conduct`.

[Gonzalo-Mier]

Hi @Batalex,

My comment was more related with correct info related to the project than giving reasons to dismiss the CovPlan. I would love to see it progress. Answering your comments:

Though we do try to avoid duplication of efforts (hence our question on similar packages), we do not position ourselves as an authority on which package should be the reference.

Nor my intention either. More, better!

As we already decided that CovPlan was in scope, we most likely will proceed with the review.

Of course, it is certainly a nice addition to the open-source ecosystem and @sanjeevrs2000 is doing an awesome job.

If anything, I would love for this GH issue to be the starting point of a collaborative effort that would benefit everyone.
If you are interested and available, please let me know!

I don't have too much free time, but I can help if needed. Please, contact me for any collaboration :)

[sanjeevrs2000]

Hi @Gonzalo-Mier, thanks again for your support. I am not a software developer myself so I have limited time as well. Will be happy to collaborate if required.

I don't have too much free time, but I can help if needed. Please, contact me for any collaboration :)

@Batalex, if it is decided that it is under scope for a review, we shall try to meet these requirements as soon as possible.

Some are really trivial (like adding a CONTRIBUTING.md or restructuring the readme using the suggestion below), others require additional work

[sanjeevrs2000]

Hi @Batalex,
I've added tests and updated the documentation as per the recommendations. Hopefully, this is enough to get started with the review now. Let me know if you find any other areas for improvement.

[Batalex]

Hi @sanjeevrs2000,
Thank you for your work on the package. There are still some things missing before I can give the go for the review.

Documentation

Since you are using mkdocs, I advise you to take a look at https://mkdocstrings.github.io/. It is a plugin that automatically picks up the docstrings to embed them in your documentation. The reason why I ask you to do that is because it will help you keep your code base and your documentation in sync.
Right now, the API reference looks like it's been written manually, and it is a problem. See, the code base is already out of sync with the documentation, and this issue will only continue to grow with the code base and the number of contributors to the project.

I also noticed a lack of consistency in the docstrings formats: some use Numpy/Google convention, others use the classic Python one I linked in my previous post. The function linked above uses neither.

You might want to explicitly list the development dependencies one needs to work on the project. It happens that I am quite familiar with mkdocs so I already know how to build the documentations, but that most likely not the case for everyone.
To do so, you may:

• add mkdocs (and mkdocstrings 👼 ) to the pyproject.toml file using the optional deps field (since you are using the setuptools build backend).
• document somewhere how to build the docs (contributing.md)

Tests and automation

I am glad to see that you added tests, but we need to go one step further. Because tests are only as useful as their consistent runs, we need to integrate them into GitHub.
Even before that, same as the previous section, it is a good idea to include a mention of how to run the tests in your contributing.md file. Same as above, you will need to explicitly state your test dependencies if you have any.

Back to GitHub, the aim of the continuous integration (CI), is to make sure that you do not introduce any regression to the code base, using the tests you wrote. By making GitHub run your tests on every pull request (and I advise you to use this workflow from now on even if you are the sole contributor), you can merge new additions to the code base more confidently.

We wrote a guide for that, this is a great starting point.

They are a few more things we could work on, but I don't want to move the goal posts further with every interaction, so I'll leave it there for now.