Robotics Toolbox for Python
Status & Project Health
Ecosystem & Dependencies
Contents
Synopsis
This toolbox brings robotics-specific functionality to Python, and leverages
Python's advantages of portability, ubiquity and support, and the capability of
the open-source ecosystem for linear algebra (numpy, scipy), graphics
(matplotlib, three.js, WebGL), interactive development (Jupyter, JupyterLab,
mybinder.org), and documentation (sphinx).
The Toolbox provides tools for representing the kinematics and dynamics of
serial-link manipulators - you can easily create your own in Denavit-Hartenberg
form, import a URDF file, or use over 50 supplied models for well-known
contemporary robots from Franka-Emika, Kinova, Universal Robotics, Rethink as
well as classical robots such as the Puma 560 and the Stanford arm.
The Toolbox contains fast implementations of kinematic operations. The forward
kinematics and the manipulator Jacobian can be computed in less than 1 microsecond
while numerical inverse kinematics can be solved in as little as 4 microseconds.
The toolbox also supports mobile robots with functions for robot motion models
(unicycle, bicycle), path planning algorithms (bug, distance transform, D*,
PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter),
map building (EKF) and simultaneous localization and mapping (EKF).
The Toolbox provides:
- code that is mature and provides a point of comparison for other
implementations of the same algorithms;
- routines which are generally written in a straightforward manner which
allows for easy understanding, perhaps at the expense of computational
efficiency;
- source code which can be read for learning and teaching;
- backward compatability with the Robotics Toolbox for MATLAB
The Toolbox leverages the Spatial Maths Toolbox for Python to
provide support for data types such as SO(n) and SE(n) matrices, quaternions, twists and spatial vectors.
Getting going
You will need Python >= 3.10
Using pip
Install a snapshot from PyPI
pip install roboticstoolbox-python
Available options are:
swift install Swift, a web-based visualizerqp install quadratic-programming IK dependencies (qpsolvers, quadprog)collision install collision checking with coal and trimeshtool install IPython and pygments, needed to run the rtbtool interactive shellik install SymPy and python-flint, to derive analytic inverse kinematics (robot.analytic_ik())all install swift, qp, collision, and tool. It does not include ik, since SymPy is large and only needed to derive an analytic solver
Windows note: coal does not publish Windows wheels on PyPI, so the
collision/all extras skip it there and collision checking is
unavailable via pip on Windows. It's available via
conda install -c conda-forge coal-python if needed. Everything else in
the Toolbox works normally.
Put the options in a comma separated list like
pip install roboticstoolbox-python[optionlist]
If you want the Swift visualizer, install the swift extra.
Install matrix:
This is the beginning of the README. Read the rest at the original. Read the full README ↗
