{"id":17321979,"url":"https://github.com/petercorke/rvc3-python","last_synced_at":"2025-05-15T01:07:59.433Z","repository":{"id":39596706,"uuid":"344303476","full_name":"petercorke/RVC3-python","owner":"petercorke","description":"Code examples for Robotics, Vision \u0026 Control 3rd edition in Python","archived":false,"fork":false,"pushed_at":"2024-12-16T06:27:04.000Z","size":85431,"stargazers_count":501,"open_issues_count":7,"forks_count":117,"subscribers_count":12,"default_branch":"main","last_synced_at":"2025-05-14T04:53:15.414Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/petercorke.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-03-04T00:33:20.000Z","updated_at":"2025-05-09T07:07:12.000Z","dependencies_parsed_at":"2024-12-14T09:09:05.645Z","dependency_job_id":"01317110-0dc2-4120-8675-8136f702164e","html_url":"https://github.com/petercorke/RVC3-python","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/petercorke%2FRVC3-python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/petercorke%2FRVC3-python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/petercorke%2FRVC3-python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/petercorke%2FRVC3-python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/petercorke","download_url":"https://codeload.github.com/petercorke/RVC3-python/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254254042,"owners_count":22039792,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-15T13:40:32.553Z","updated_at":"2025-05-15T01:07:54.423Z","avatar_url":"https://github.com/petercorke.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Robotics, Vision \u0026 Control: 3rd edition in Python (2023)\n[![A Python Robotics Package](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/py_collection.min.svg)](https://github.com/petercorke/robotics-toolbox-python)\n[![QUT Centre for Robotics Open Source](https://github.com/qcr/qcr.github.io/raw/master/misc/badge.svg)](https://qcr.github.io)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n[![PyPI version](https://badge.fury.io/py/rvc3python.svg)](https://badge.fury.io/py/rvc3python)\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/rvc3python.svg)\n[![PyPI - Downloads](https://img.shields.io/pypi/dw/rvc3python)](https://pypistats.org/packages/rvc3python)\n\n\u003ctable style=\"border:0px\"\u003e\n\u003ctr style=\"border:0px\"\u003e\n\u003ctd style=\"border:0px\"\u003e\n\u003cimg src=\"https://github.com/petercorke/RVC3-python/raw/main/doc/frontcover.png\" alt=\"Front cover 978-3-031-06468-5_5208\" width=\"300\"\u003e\n\u003c/td\u003e\n\u003ctd style=\"border:0px\"\u003e\nWelcome to the online hub for the book:\n\u003cul type=\"none\"\u003e\n\u003cli\u003e\u003cb\u003eRobotics, Vision \u0026 Control\u003c/b\u003e: fundamental algorithms in Python (3rd edition) \n\u003cli\u003ePeter Corke, published by Springer-Nature 2023.\u003c/li\u003e\n\u003cli\u003e\u003cb\u003eISBN\u003c/b\u003e 978-3-031-06468-5 (hardcopy), 978-3-031-06469-2 (eBook)\u003c/li\u003e\n\u003cli\u003e\u003cb\u003eDOI\u003c/b\u003e \u003ca href=\"https://doi.org/10.1007/978-3-031-06469-2\"\u003e10.1007/978-3-031-06469-2\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cbr\u003e\u003cbr\u003e\n\u003cp\u003eReport an issue with the book or its supporting code \u003ca href=\"https://github.com/petercorke/RVC3-python/issues/new/choose\"\u003ehere\u003c/a\u003e.\u003c/p\u003e\n\n\u003cp\u003eKnown errata for the book can be viewed \u003ca href=\"https://github.com/petercorke/RVC3-python/wiki/Errata\"\u003ehere\u003c/a\u003e.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\nThis book uses many examples based on the following open-source Python packages\n\n\u003ca href=\"https://github.com/petercorke/robotics-toolbox-python\"\u003e\u003cimg alt=\"Robotics Toolbox for Python\" src=\"https://github.com/petercorke/robotics-toolbox-python/raw/master/docs/figs/RobToolBox_RoundLogoB.png\" width=\"130\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/petercorke/machinevision-toolbox-python\"\u003e\u003cimg alt=\"Machine Vision Toolbox for Python\" src=\"https://github.com/petercorke/machinevision-toolbox-python/raw/master/figs/VisionToolboxLogo_NoBackgnd@2x.png\" width=\"150\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/petercorke/spatialmath-python\"\u003e\u003cimg alt=\"Spatial Maths Toolbox for Python\" src=\"https://github.com/petercorke/spatialmath-python/raw/master/docs/figs/CartesianSnakes_LogoW.png\" width=\"130\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/petercorke/bdsim\"\u003e\u003cimg alt=\"Block diagram simulation for Python\" src=\"https://github.com/petercorke/bdsim/raw/master/figs/BDSimLogo_NoBackgnd@2x.png\" width=\"250\"\u003e\u003c/a\u003e\n\n**Robotics Toolbox for Python**, **Machine Vision Toolbox for Python**, **Spatial Maths Toolbox for Python**, **Block Diagram Simulation for Python**.  These in turn have dependencies on other packages created by the author and\nthird parties.\n\n## Installing the package\n\nThis package provides a simple one-step installation of *all* the required Toolboxes\n```shell\npip install rvc3python\n```\nor\n```shell\nconda install rvc3python\n```\n\nThere are a lot of dependencies and this might take a minute or so.  You now have a very\npowerful computing environment for robotics and computer vision.\n\n### Python version\n\nGiven the rapid rate of language additions, particularly around type hinting, use at\nleast Python 3.8.  Python 3.7 goes end of life in June 2023.\n\nNot all package dependencies will work with the latest release of Python.  In particular, check:\n* [PyTorch](https://pypi.org/project/torch/) used for segmentation examples in Chapter 12\n* [Open3D](https://pypi.org/project/open3d), used for point cloud examples in Chapter 14.\n\n### Installing into a Conda environment\n\nIt's probably a good idea to create a virtual environment to keep this package\nand its dependencies separated from your other Python code and projects.  If you've\nnever used virtual environments before this might be a good time to start, and it\nis really easy [using Conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html):\n```shell\nconda create -n RVC3 python=3.10\nconda activate RVC3\npip install rvc3python\n```\n\n### Installing deep learning tools\n\nChapter 11 has some deep learning examples based on PyTorch.  If you don't have \nPyTorch installed you can use the `pytorch` install option\n```shell\npip install rvc3python[pytorch]\n```\nor\n```shell\nconda install rvc3python\n```\n## Using the Toolboxes\n\nThe simplest way to get going is to use the command line tool\n\n```shell\n$ rvctool\n ____       _           _   _             __     ___     _                ___      ____            _             _   _____ \n|  _ \\ ___ | |__   ___ | |_(_) ___ ___    \\ \\   / (_)___(_) ___  _ __    ( _ )    / ___|___  _ __ | |_ _ __ ___ | | |___ / \n| |_) / _ \\| '_ \\ / _ \\| __| |/ __/ __|    \\ \\ / /| / __| |/ _ \\| '_ \\   / _ \\/\\ | |   / _ \\| '_ \\| __| '__/ _ \\| |   |_ \\ \n|  _ \u003c (_) | |_) | (_) | |_| | (__\\__ \\_    \\ V / | \\__ \\ | (_) | | | | | (_\u003e  \u003c | |__| (_) | | | | |_| | | (_) | |  ___) |\n|_| \\_\\___/|_.__/ \\___/ \\__|_|\\___|___( )    \\_/  |_|___/_|\\___/|_| |_|  \\___/\\/  \\____\\___/|_| |_|\\__|_|  \\___/|_| |____/ \n                                      |/                                                                                   \n                                                                                 \nfor Python (RTB==1.1.0, MVTB==0.9.5, SG==1.1.7, SMTB==1.1.7, NumPy==1.24.2, SciPy==1.10.1, Matplotlib==3.7.1)\n\n    import math\n    import numpy as np\n    from scipy import linalg, optimize\n    import matplotlib.pyplot as plt\n    from spatialmath import *\n    from spatialmath.base import *\n    from spatialmath.base import sym\n    from spatialgeometry import *\n    from roboticstoolbox import *\n    from machinevisiontoolbox import *\n    import machinevisiontoolbox.base as mvb\n    \n    # useful variables\n    from math import pi\n    puma = models.DH.Puma560()\n    panda = models.DH.Panda()\n\n    func/object?       - show brief help\n    help(func/object)  - show detailed help\n    func/object??      - show source code\n\nResults of assignments will be displayed, use trailing ; to suppress\n    \nPython 3.10.9 | packaged by conda-forge | (main, Feb  2 2023, 20:24:27) [Clang 14.0.6 ]\nType 'copyright', 'credits' or 'license' for more information\nIPython 8.11.0 -- An enhanced Interactive Python. Type '?' for help.\n\n\n\u003e\u003e\u003e \n```\n\nThis provides an interactive Python\n([IPython](https://ipython.readthedocs.io/en/stable)) session with all the Toolboxes and\nsupporting packages imported, and ready to go.  It's a highly capable, convenient, and\n\"MATLAB-like\" workbench environment for robotics and computer vision.\n\nFor example to load an ETS model of a Panda robot, solve a forward kinematics\nand inverse kinematics problem, and an interactive graphical display is simply:\n\n```python\n\u003e\u003e\u003e panda = models.ETS.Panda()\nERobot: Panda (by Franka Emika), 7 joints (RRRRRRR)\n┌─────┬───────┬───────┬────────┬─────────────────────────────────────────────┐\n│link │ link  │ joint │ parent │             ETS: parent to link             │\n├─────┼───────┼───────┼────────┼─────────────────────────────────────────────┤\n│   0 │ link0 │     0 │ BASE   │ tz(0.333) ⊕ Rz(q0)                          │\n│   1 │ link1 │     1 │ link0  │ Rx(-90°) ⊕ Rz(q1)                           │\n│   2 │ link2 │     2 │ link1  │ Rx(90°) ⊕ tz(0.316) ⊕ Rz(q2)                │\n│   3 │ link3 │     3 │ link2  │ tx(0.0825) ⊕ Rx(90°) ⊕ Rz(q3)               │\n│   4 │ link4 │     4 │ link3  │ tx(-0.0825) ⊕ Rx(-90°) ⊕ tz(0.384) ⊕ Rz(q4) │\n│   5 │ link5 │     5 │ link4  │ Rx(90°) ⊕ Rz(q5)                            │\n│   6 │ link6 │     6 │ link5  │ tx(0.088) ⊕ Rx(90°) ⊕ tz(0.107) ⊕ Rz(q6)    │\n│   7 │ @ee   │       │ link6  │ tz(0.103) ⊕ Rz(-45°)                        │\n└─────┴───────┴───────┴────────┴─────────────────────────────────────────────┘\n\n┌─────┬─────┬────────┬─────┬───────┬─────┬───────┬──────┐\n│name │ q0  │ q1     │ q2  │ q3    │ q4  │ q5    │ q6   │\n├─────┼─────┼────────┼─────┼───────┼─────┼───────┼──────┤\n│  qr │  0° │ -17.2° │  0° │ -126° │  0° │  115° │  45° │\n│  qz │  0° │  0°    │  0° │  0°   │  0° │  0°   │  0°  │\n└─────┴─────┴────────┴─────┴───────┴─────┴───────┴──────┘\n\n\u003e\u003e\u003e panda.fkine(panda.qz)\n   0.7071    0.7071    0         0.088     \n   0.7071   -0.7071    0         0         \n   0         0        -1         0.823     \n   0         0         0         1      \n\u003e\u003e\u003e panda.ikine_LM(SE3.Trans(0.4, 0.5, 0.2) * SE3.Ry(pi/2))\nIKSolution(q=array([  -1.849,   -2.576,   -2.914,     1.22,   -1.587,    2.056,   -1.013]), success=True, iterations=13, searches=1, residual=3.3549072615799585e-10, reason='Success')\n\u003e\u003e\u003e panda.teach(panda.qz)\n```\n![](https://github.com/petercorke/RVC3-python/raw/main/doc/panda_noodle.png)\n\nComputer vision is just as easy.  For example, we can import an image, blur it\nand display it alongside the original\n```python\n\u003e\u003e\u003e mona = Image.Read(\"monalisa.png\")\n\u003e\u003e\u003e Image.Hstack([mona, mona.smooth(sigma=5)]).disp()\n```\n![](https://github.com/petercorke/machinevision-toolbox-python/raw/master/figs/mona%2Bsmooth.png)\n\nor load two images of the same scene, compute SIFT features and display putative\nmatches\n```python\n\u003e\u003e\u003e sf1 = Image.Read(\"eiffel-1.png\", mono=True).SIFT()\n\u003e\u003e\u003e sf2 = Image.Read(\"eiffel-2.png\", mono=True).SIFT()\n\u003e\u003e\u003e matches = sf1.match(sf2)\n\u003e\u003e\u003e matches.subset(100).plot(\"w\")\n```\n![](https://github.com/petercorke/machinevision-toolbox-python/raw/master/figs/matching.png)\n\n`rvctool` is a wrapper around\n[IPython](https://ipython.readthedocs.io/en/stable) where:\n- robotics and vision functions and classes can be accessed without needing\n  package prefixes\n- results are displayed by default like MATLAB does, and like MATLAB you need to\n  put a semicolon on the end of the line to prevent this\n- the prompt is the standard Python REPL prompt `\u003e\u003e\u003e` rather than the IPython\n  prompt, this can be overridden by a command-line switch\n- allows cutting and pasting in lines from the book, and prompt characters are\n  ignored\n\nThe Robotics, Vision \u0026 Control book uses `rvctool` for all the included\nexamples.\n\n`rvctool` imports the all the above mentioned packages using `import *` which is\nnot considered best Python practice.  It is very convenient for interactive\nexperimentation, but in your own code you can handle the imports as you see\nfit.\n\n### Cutting and pasting\n\nIPython is very forgiving when it comes to cutting and pasting in blocks of Python\ncode.  It will strip off the `\u003e\u003e\u003e` prompt character and ignore indentation.  The normal\npython REPL is not so forgiving.  IPython also maintains a command history and\nallows command editing.\n### Simple scripting\nYou can write very simple scripts, for example `test.py` is\n\n```python\nT = puma.fkine(puma.qn)\nsol = puma.ikine_LM(T)\nsol.q\npuma.plot(sol.q);\n```\n\nthen \n\n```shell\n$ rvctool test.py\n   0         0         1         0.5963    \n   0         1         0        -0.1501    \n  -1         0         0         0.6575    \n   0         0         0         1         \n\nIKSolution(q=array([7.235e-08,  -0.8335,  0.09396,    3.142,   0.8312,   -3.142]), success=True, iterations=15, searches=1, residual=1.406125546650288e-07, reason='Success')\narray([7.235e-08,  -0.8335,  0.09396,    3.142,   0.8312,   -3.142])\nPyPlot3D backend, t = 0.05, scene:\n  robot: Text(0.0, 0.0, 'Puma 560')\n\u003e\u003e\u003e\n```\nand you are dropped into an IPython session after the script has run.\n\n## Issues running on Apple Silicon\n\nCheck out the [wiki page](https://github.com/petercorke/RVC3-python/wiki/Running-on-Apple-Silicon).\n\n## Using Jupyter and Colab\n\nGraphics and animations are problematic in these environments, some things work\nwell, some don't.  As much as possible I've tweaked the Jupyter notebooks to work\nas best they can in these environments.\n\nFor local use the [Jupyter plugin for Visual Studio Code](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) is pretty decent.  Colab suffers\nfrom old versions of major packages (though they are getting better at keeping up to date)\nand animations can suffer from slow update over the network.\n## Other command line tools\n\nAdditional command line tools available (from the Robotics Toolbox) include:\n- `eigdemo`, animation showing linear transformation of a rotating unit vector\n  which demonstrates eigenvalues and eigenvectors.\n- `tripleangledemo`, Swift visualization that lets you experiment with various triple-angle sequences.\n- `twistdemo`, Swift visualization that lets you experiment with 3D twists. The screw axis is the blue rod and you can\n   position and orient it using the sliders, and adjust its pitch. Then apply a rotation\n   about the screw using the bottom slider.\n# Block diagram models\n\n\u003ca href=\"https://github.com/petercorke/bdsim\"\u003e\u003cimg\nsrc=\"https://github.com/petercorke/bdsim/raw/master/figs/BDSimLogo_NoBackgnd%402x.png\"\nalt=\"bdsim logo\" width=\"300\"\u003e\u003c/a\u003e\n\nBlock diagram models are key to the pedagogy of the RVC3 book and 25 models are\nincluded. To simulate these models we use the Python package\n[bdsim](https://github.com/petercorke/bdsim) which can run models:\n\n- written in Python using\n  [bdsim](https://github.com/petercorke/bdsim#getting-started) blocks and\n  wiring.\n- created graphically using\n  [bdedit](https://github.com/petercorke/bdsim#bdedit-the-graphical-editing-tool)\n  and saved as a `.bd` (JSON format) file.\n\nThe models are included in the `RVC3` package when it is installed and `rvctool`\nadds them to the module search path.  This means you can invoke them from\n`rvctool` by\n```python\n\u003e\u003e\u003e %run -m vloop_test\n```\n\nIf you want to directly access the folder containing the models, the command\nline tool\n```shell\nbdsim_path\n```\nwill display the full path to where they have been installed in the Python\npackage tree.\n\n\n# Additional book resources\n\n\u003cimg src=\"https://github.com/petercorke/RVC3-python/raw/main/doc/frontcover.png\" alt=\"Front cover 978-3-031-06468-5_5208\" width=\"100\"\u003e\n\nThis GitHub repo provides additional resources for readers including:\n- Jupyter notebooks containing all code lines from each chapter, see\n  the [`notebooks`](notebooks) folder\n- The code to produce every Python/Matplotlib (2D) figure in the book, see the [`figures`](figures) folder\n- 3D points clouds from chapter 14, and the code to create them, see\n  the [`pointclouds`](../pointclouds) folder.\n- 3D figures from chapters 2-3, 7-9, and the code to create them, see the [`3dfigures`](../3dfigures) folder.\n- All example scripts, see the [`examples`](examples) folder.\n- To run the visual odometry example in Sect. 14.8.3 you need to download two image sequence, each over 100MB, [see the instructions here](https://github.com/petercorke/machinevision-toolbox-python/blob/master/mvtb-data/README.md#install-big-image-files). \n\nTo get that material you must clone the repo\n```shell\ngit clone https://github.com/petercorke/RVC3-python.git\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpetercorke%2Frvc3-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpetercorke%2Frvc3-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpetercorke%2Frvc3-python/lists"}