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PyBullet Industrial

PyBullet Industrial: A process-aware robot simulation - Published in JOSS (2023)

https://github.com/wbk-robotics/pybullet_industrial

Science Score: 100.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: joss.theoj.org
  • ✓
    Committers with academic emails
    3 of 5 committers (60.0%) from academic institutions
  • ✓
    Institutional organization owner
    Organization wbk-robotics has institutional domain (www.wbk.kit.edu)
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

industrial-automation robotics simulation-framework
Last synced: 4 months ago · JSON representation ·

Repository

A simulation package extending pybullet for industrial robot applications

Basic Info
Statistics
  • Stars: 45
  • Watchers: 3
  • Forks: 7
  • Open Issues: 17
  • Releases: 5
Topics
industrial-automation robotics simulation-framework
Created over 3 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Citation

README.md

pybullet_industrial_logo DOI codecov codiga Documentation Status

Pybulletindustrial is a process-aware robot simulation. It aims to enable scientists and researchers to easily simulate robotics scenarios where a robot is participating in a manufacturing process. It achieves this by combining the world of classical robot simulations with the world of industrial processes. The library is capable of simulating different manufacturing tools and workpieces, as well as the robot itself. With the help of the pybulletindustrial package you will be able to:

  • simulate additive manufacturing processes
  • simulate milling processes and how the resulting forces impact the robot
  • simulating paint coating scenarios
  • simulate the handling of complex tasks using a variety of grippers

example_gif

Documentation

You can find the documentation here.

Getting Started

There are two ways to get started with the library. The first is to use the newest source version from the repository. The second is to use the latest release version from pip. The source version is the most up-to-date, but it is also the most unstable. The release version is the most stable, but it is also the least up-to-date. The release version is recommended for most users, but the source version is recommended for developers.

Getting started with the release version

The release version is the most stable version of the library. It is recommended for most users. To install the release version, run the following command:

pip install pybullet_industrial

Getting started with the source version

The source version is the most up-to-date version of the library. It is recommended for developers. To install the source version from the repository, run the following commands:

git clone https://github.com/WBK-Robotics/pybullet_industrial cd pybullet_industrial pip install src/

Note that if you are on windows, you may need to use the command pip install src\\ instead. And depending on how you have installed your python environment, you may need to first install wheel using pip install wheel.

Citing the Package

If you find the package useful, please consider citing it using the citation information on the right side of this page.

Owner

  • Name: wbk Institute of Production Science
  • Login: WBK-Robotics
  • Kind: organization
  • Location: Germany

The wbk Institute for Production Science is dedicated to application-oriented research, teaching, and innovation in the field of production science at KIT

JOSS Publication

PyBullet Industrial: A process-aware robot simulation
Published
May 18, 2023
DOI
Volume 8, Issue 85, Page 5174
Authors
Jan Baumgärtner ORCID
wbk Institute of Production Science
Malte Hansjosten
wbk Institute of Production Science
Dominik Schönhofen
Independent Researcher
Prof. Dr.-Ing. Jürgen Fleischer ORCID
wbk Institute of Production Science
Editor
Adi Sinn ORCID
Tags
Python robotics simulation milling force calculation 3D printing production processes
View PDF Review Thread Software Archive

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Baumgärtner
  given-names: Jan
  orcid: "https://orcid.org/0000-0002-7825-3476"
- family-names: Hansjosten
  given-names: Malte
- family-names: Schönhofen
  given-names: Dominik
- family-names: Fleischer
  given-names: Prof. Dr.-Ing. Jürgen
  orcid: "https://orcid.org/0000-0003-0961-7675"
doi: 10.5281/zenodo.7833292
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Baumgärtner
    given-names: Jan
    orcid: "https://orcid.org/0000-0002-7825-3476"
  - family-names: Hansjosten
    given-names: Malte
  - family-names: Schönhofen
    given-names: Dominik
  - family-names: Fleischer
    given-names: Prof. Dr.-Ing. Jürgen
    orcid: "https://orcid.org/0000-0003-0961-7675"
  date-published: 2023-05-18
  doi: 10.21105/joss.05174
  issn: 2475-9066
  issue: 85
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5174
  title: "PyBullet Industrial: A process-aware robot simulation"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05174"
  volume: 8
title: "PyBullet Industrial: A process-aware robot simulation"

GitHub Events

Total
  • Create event: 6
  • Release event: 2
  • Issues event: 4
  • Watch event: 8
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 191
  • Pull request event: 1
  • Pull request review event: 16
  • Pull request review comment event: 16
  • Fork event: 2
Last Year
  • Create event: 6
  • Release event: 2
  • Issues event: 4
  • Watch event: 8
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 191
  • Pull request event: 1
  • Pull request review event: 16
  • Pull request review comment event: 16
  • Fork event: 2

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 521
  • Total Committers: 5
  • Avg Commits per committer: 104.2
  • Development Distribution Score (DDS): 0.267
Past Year
  • Commits: 37
  • Committers: 3
  • Avg Commits per committer: 12.333
  • Development Distribution Score (DDS): 0.135
Top Committers
Name Email Commits
Jan Baumgärtner c****t@j****h 382
Philipp p****z@s****u 109
MaHajo 4****o 16
Dominik Schönhofen u****y@s****u 13
Cameron Devine c****e@s****u 1
Committer Domains (Top 20 + Academic)
student.kit.edu: 2 stmartin.edu: 1 jan-baumgaertner.tech: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 32
  • Total pull requests: 30
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 9
  • Total pull request authors: 5
  • Average comments per issue: 1.13
  • Average comments per pull request: 1.1
  • Merged pull requests: 25
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 months
  • Issue authors: 3
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 2.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • liquidcronos (13)
  • MaHajo (7)
  • CameronDevine (3)
  • philipp1604 (3)
  • sea-bass (2)
  • virtuamechanica (1)
  • wirthbenjamin (1)
  • SebWiegert (1)
  • liqingxin (1)
  • koeri246 (1)
  • CGL-learner (1)
Pull Request Authors
  • liquidcronos (18)
  • philipp1604 (14)
  • koeri246 (2)
  • MaHajo (1)
  • CameronDevine (1)
Top Labels
Issue Labels
enhancement (19) bug (12) documentation (1)
Pull Request Labels
enhancement (1)

Packages

  • Total packages: 2
  • Total downloads: unknown
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 10
proxy.golang.org: github.com/WBK-Robotics/pybullet_industrial
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 4 months ago
proxy.golang.org: github.com/wbk-robotics/pybullet_industrial
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 4 months ago

Dependencies

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