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‎.github/workflows/future_testing.yml

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strategy:
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matrix:
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os: [windows-latest, ubuntu-latest, macos-latest]
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python-version: [3.7, 3.8, 3.9]
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python-version: [3.7, 3.8, 3.9, '3.10']
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steps:
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- name: Set up Python ${{ matrix.python-version }}
@@ -28,18 +28,21 @@ jobs:
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- name: Checkout Swift
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uses: actions/checkout@v2
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with:
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ref: future
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repository: jhavl/swift
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path: swift
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- name: Checkout Spatialmath
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uses: actions/checkout@v2
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with:
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ref: future
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repository: petercorke/spatialmath-python
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path: sm
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- name: Checkout Spatialgeometry
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uses: actions/checkout@v2
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with:
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ref: future
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repository: jhavl/spatialgeometry
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path: sg
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‎.gitignore

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*.doctree
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# Vim
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*.sw*
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‎README.md

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@@ -236,11 +236,26 @@ Or you can run them, and experiment with them, at [mybinder.org](https://mybinde
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The toolbox is incredibly useful for developing and prototyping algorithms for research, thanks to the exhaustive set of well documented and mature robotic functions exposed through clean and painless APIs. Additionally, the ease at which a user can visualize their algorithm supports a rapid prototyping paradigm.
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Check out our ICRA 2021 paper on [IEEE Xplore](https://ieeexplore.ieee.org/document/9561366) or get the PDF from [Peter's website](https://petercorke.com/download/31/python-tools/1296/python_toolbox_icra_2020-5.pdf).
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If the toolbox helped you in your research, please cite
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```
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@inproceedings{rtb,
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title={Not your grandmother’s toolbox--the Robotics Toolbox reinvented for Python},
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author={Corke, Peter and Haviland, Jesse},
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booktitle={2021 IEEE International Conference on Robotics and Automation (ICRA)},
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pages={11357--11363},
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year={2021},
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organization={IEEE}
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}
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```
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### Publication List
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J. Haviland, N. Sünderhauf and P. Corke, "**A Holistic Approach to Reactive Mobile Manipulation**,". In the video, the robot is controlled using the Robotics toolbox for Python and features a recording from the [Swift](https://github.com/jhavl/swift) Simulator.
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J. Haviland, N. Sünderhauf and P. Corke, "**A Holistic Approach to Reactive Mobile Manipulation**," in _IEEE Robotics and Automation Letters_, doi: 10.1109/LRA.2022.3146554. In the video, the robot is controlled using the Robotics toolbox for Python and features a recording from the [Swift](https://github.com/jhavl/swift) Simulator.
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[[Arxiv Paper](https://arxiv.org/abs/2109.04749)] [[Project Website](https://jhavl.github.io/holistic/)] [[Video](https://youtu.be/-DXBQPeLIV4)] [[Code Example](https://github.com/petercorke/robotics-toolbox-python/blob/master/roboticstoolbox/examples/holistic_mm_non_holonomic.py)]
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[[Arxiv Paper](https://arxiv.org/abs/2109.04749)] [[IEEE Xplore](https://ieeexplore.ieee.org/abstract/document/9695298)] [[Project Website](https://jhavl.github.io/holistic/)] [[Video](https://youtu.be/-DXBQPeLIV4)] [[Code Example](https://github.com/petercorke/robotics-toolbox-python/blob/master/roboticstoolbox/examples/holistic_mm_non_holonomic.py)]
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<p>
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<a href="https://youtu.be/-DXBQPeLIV4">

‎docs/source/arm_ets.rst

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@@ -12,21 +12,21 @@ Consider the example:
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.. runblock:: pycon
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:linenos:
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>>> from roboticstoolbox import ETS
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>>> ETS.rx(45, 'deg')
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>>> ETS.tz(0.75)
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>>> e = ETS.rx(0.3) * ETS.tz(0.75)
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>>> from roboticstoolbox import ET
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>>> ET.Rx(45, 'deg')
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>>> ET.tz(0.75)
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>>> e = ET.Rx(0.3) * ET.tz(0.75)
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>>> print(e)
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>>> e.eval()
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>>> e.fkine([])
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In lines 2-5 we defined two elementary transforms. Line 2 defines a rotation
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of 45° about the x-axis, and line 4 defines a translation of 0.75m along the z-axis.
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Compounding them in line 6, the result is the two elementary transforms in a
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sequence - an elementary transform sequence (ETS). An ETS can be arbitrarily
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long.
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Line 8 *evaluates* the sequence, substituting in values, and the result is an
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SE(3) matrix encapsulated in an ``SE3`` object.
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Line 8 *evaluates* the forward kinematics of the sequence, substituting in values,
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and the result is an SE(3) matrix encapsulated in an ``4x4`` numpy array.
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The real power comes from having variable arguments to the elementary transforms
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as shown in this example where we define a simple two link planar manipulator.
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.. runblock:: pycon
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:linenos:
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>>> from roboticstoolbox import ETS
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>>> e = ETS.rz() * ETS.tx(1) * ETS.rz() * ETS.tx(1)
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>>> from roboticstoolbox import ET
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>>> e = ET.Rz() * ET.tx(1) * ET.Rz() * ET.tx(1)
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>>> print(e)
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>>> len(e)
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>>> e[1:3]
43-
>>> e.eval([0, 0])
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>>> e.eval([90, -90], 'deg')
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>>> e.fkine([0, 0])
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>>> e.fkine([1.57, -1.57])
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Line 2 succinctly describes the kinematics in terms of elementary transforms: a rotation around the z-axis by the
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first joint angle, then a translation in the x-direction, then a rotation around
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the z-axis by the second joint angle, and finally a translation in the
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x-direction.
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Line 2 succinctly describes the kinematics in terms of elementary transforms: a
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rotation around the z-axis by the first joint angle, then a translation in the
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x-direction, then a rotation around the z-axis by the second joint angle, and
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finally a translation in the x-direction.
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Line 3 creates the elementary transform sequence, with variable transforms.
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``e`` is a single object that encapsulates a list of elementary transforms, and list like
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--------
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.. autoclass:: roboticstoolbox.robot.ETS.ETS
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:members: rx, ry, rz, tx, ty, tz, eta, n, joints, isjoint, isconstant, isrevolute, isprismatic, axis, config, __getitem__, pop, __mul__, __repr__, __str__, T, eval, compile, SE3, jacob0, hessian0
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:members: __str__, __repr__, __mul__, __getitem__, n, m, structure, joints, jointset, split, inv, compile, insert, fkine, jacob0, jacobe, hessian0, hessiane
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:undoc-members:
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:show-inheritance:
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:member-order: bysource
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ETS - 2D
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--------
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.. autoclass:: roboticstoolbox.robot.ETS.ETS2
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:members: r, tx, ty, eta, n, joints, isjoint, isconstant, isrevolute, isprismatic, axis, config, __getitem__, pop, __mul__, __repr__, __str__, T, eval, compile
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:members: __str__, __repr__, __mul__, __getitem__, n, m, structure, joints, jointset, split, inv, compile, insert, fkine, jacob0, jacobe
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:undoc-members:
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:show-inheritance:
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‎docs/source/conf.py

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import re
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# defined relative to configuration directory which is where this file conf.py lives
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sys.path.append(os.path.abspath('exts'))
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sys.path.append(os.path.abspath("exts"))
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# -- Project information -----------------------------------------------------
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project = 'Robotics Toolbox for Python'
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copyright = '2020, Jesse Haviland and Peter Corke'
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author = 'Jesse Haviland and Peter Corke'
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project = "Robotics Toolbox for Python"
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copyright = "2020, Jesse Haviland and Peter Corke"
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author = "Jesse Haviland and Peter Corke"
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# print(__file__)
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# parse version number out of setup.py
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with open('../../setup.py', encoding='utf-8') as f:
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with open("../../setup.py", encoding="utf-8") as f:
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setup_py = f.read()
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m = re.search("version='([0-9\.]*)',", setup_py, re.MULTILINE)
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# Add any Sphinx extension module names here, as strings. They can be
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.todo',
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'sphinx.ext.viewcode',
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'sphinx.ext.mathjax',
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'sphinx.ext.coverage',
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'sphinx.ext.doctest',
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'sphinx.ext.inheritance_diagram',
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'sphinx_autorun',
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'blockname',
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]
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extensions = [
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"sphinx.ext.autodoc",
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"sphinx.ext.todo",
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"sphinx.ext.viewcode",
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"sphinx.ext.mathjax",
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"sphinx.ext.coverage",
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"sphinx.ext.doctest",
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"sphinx.ext.inheritance_diagram",
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"sphinx_autorun",
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"blockname",
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"sphinx.ext.intersphinx",
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]
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autosummary_generate = True
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autodoc_member_order = 'bysource'
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autodoc_member_order = "bysource"
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ['_templates']
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templates_path = ["_templates"]
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exclude_patterns = ['test_*']
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exclude_patterns = ["test_*"]
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# options for spinx_autorun, used for inline examples
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# choose UTF-8 encoding to allow for Unicode characters, eg. ansitable
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# Python session setup, turn off color printing for SE3, set NumPy precision
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autorun_languages = {}
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autorun_languages['pycon_output_encoding'] = 'UTF-8'
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autorun_languages['pycon_input_encoding'] = 'UTF-8'
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autorun_languages['pycon_runfirst'] = """
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autorun_languages["pycon_output_encoding"] = "UTF-8"
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autorun_languages["pycon_input_encoding"] = "UTF-8"
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autorun_languages[
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"pycon_runfirst"
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] = """
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from spatialmath import SE3
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SE3._color = False
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import numpy as np
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# -- Options for HTML output -------------------------------------------------
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html_theme = 'sphinx_rtd_theme'
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html_theme = "sphinx_rtd_theme"
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html_theme_options = {
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#'github_user': 'petercorke',
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#'github_repo': 'spatialmath-python',
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#'logo_name': False,
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'logo_only': False,
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'display_version': True,
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'prev_next_buttons_location': 'both',
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'analytics_id': 'G-11Q6WJM565',
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'style_external_links': True,
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}
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html_logo = '../figs/RobToolBox_RoundLogoB.png'
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html_last_updated_fmt = '%d-%b-%Y'
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"logo_only": False,
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"display_version": True,
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"prev_next_buttons_location": "both",
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"analytics_id": "G-11Q6WJM565",
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"style_external_links": True,
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}
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html_logo = "../figs/RobToolBox_RoundLogoB.png"
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html_last_updated_fmt = "%d-%b-%Y"
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show_authors = True
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# mathjax_config = {
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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html_static_path = ["_static"]
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html_css_files = [
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'css/custom.css',
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"css/custom.css",
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]
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# autodoc_mock_imports = ["numpy", "scipy"]
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# autodoc_mock_imports = ["numpy", "scipy"]
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# -- Options for LaTeX/PDF output --------------------------------------------
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latex_engine = 'xelatex'
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latex_engine = "xelatex"
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# maybe need to set graphics path in here somewhere
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# \graphicspath{{figures/}{../figures/}{C:/Users/me/Documents/project/figures/}}
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# https://stackoverflow.com/questions/63452024/how-to-include-image-files-in-sphinx-latex-pdf-files
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latex_elements = {
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# The paper size ('letterpaper' or 'a4paper').
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'papersize': 'a4paper',
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"papersize": "a4paper",
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#'releasename':" ",
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# Sonny, Lenny, Glenn, Conny, Rejne, Bjarne and Bjornstrup
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# 'fncychap': '\\usepackage[Lenny]{fncychap}',
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'fncychap': '\\usepackage{fncychap}',
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'maketitle': "blah blah blah"
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"fncychap": "\\usepackage{fncychap}",
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"maketitle": "blah blah blah",
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}
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# Use RVC book notation for maths
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# see https://stackoverflow.com/questions/9728292/creating-latex-math-macros-within-sphinx
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mathjax_config = {
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'TeX': {
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'Macros': {
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"TeX": {
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"Macros": {
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# RVC Math notation
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# - not possible to do the if/then/else approach
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# - subset only
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# quaternions
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"q": r"\mathring{q}",
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"fq": [r"\presup{#1}\mathring{q}", 1],
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}
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}
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}
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}
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intersphinx_mapping = {
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"numpy": ("http://docs.scipy.org/doc/numpy/", None),
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"scipy": ("http://docs.scipy.org/doc/scipy/reference/", None),
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"matplotlib": ("http://matplotlib.sourceforge.net/", None),
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}
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# 'python': ('http://docs.python.org/2', None),

‎docs/source/mobile.rst

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mobile_vehicle
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mobile_vehicle_animation
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mobile_drivers
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mobile_reactive
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mobile_planner
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mobile_EKF
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mobile_SLAM

‎docs/source/mobile_SLAM.rst

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Localization and Mapping
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========================
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These classes support simulation of vehicle and map estimation in a simple
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planar world with point landmarks.
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State estimation
9+
----------------
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Two state estimators are included.
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Extended Kalman filter
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^^^^^^^^^^^^^^^^^^^^^^
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The EKF is capable of vehicle localization, map estimation or SLAM.
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.. autoclass:: roboticstoolbox.mobile.EKF
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:undoc-members:
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:show-inheritance:
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:inherited-members:
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:special-members: __init__
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Particle filter
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^^^^^^^^^^^^^^^
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The particle filter is capable of map-based vehicle localization.
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.. autoclass:: roboticstoolbox.mobile.ParticleFilter
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:undoc-members:
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:show-inheritance:
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:inherited-members:
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:special-members: __init__
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Sensor models
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-------------
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.. autoclass:: roboticstoolbox.mobile.RangeBearingSensor
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:undoc-members:
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:show-inheritance:
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:inherited-members:
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:special-members: __init__
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.. autoclass:: roboticstoolbox.mobile.SensorBase
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:undoc-members:
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:show-inheritance:
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:inherited-members:
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:special-members: __init__
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Map models
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----------
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.. automodule:: roboticstoolbox.mobile.landmarkmap
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:undoc-members:
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:show-inheritance:
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:inherited-members:
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:special-members: __init__
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