Package: roboticstoolbox-python
Robotics Toolbox for PythonA Python implementation of theRobotics Toolbox for MATLAB®GitHub repositoryDocumentationICRA PaperWiki (examples and details)ContentsSynopsisGetting goingTutorialsCode ExamplesToolbox Research ApplicationsToolbox ICRA Paper and Citation InfoUsing the Toolbox in your Open Source Code?Common Issues and SolutionsSynopsisThis 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 30 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 MATLABThe Toolbox leverages theSpatial Maths Toolbox for Pythonto
provide support for data types such as SO(n) and SE(n) matrices, quaternions, twists and spatial vectors.Getting goingYou will need Python >= 3.6Using pipInstall a snapshot from PyPIpip3installroboticstoolbox-pythonAvailable options are:collisioninstall collision checking withpybulletPut the options in a comma separated list likepip3installroboticstoolbox-python[optionlist]Swift, a web-based visualizer, is
installed as part of Robotics Toolbox.From GitHubTo install the bleeding-edge version from GitHubgitclonehttps://github.com/petercorke/robotics-toolbox-python.gitcdrobotics-toolbox-python
pip3install-e.TutorialsDo you want to learn about manipulator kinematics, differential kinematics, inverse-kinematics and motion control? Have a look at ourtutorial.
This tutorial comes with two articles to cover the theory and 12 Jupyter Notebooks providing full code implementations and examples. Most of the Notebooks are also Google Colab compatible allowing them to run online.Code ExamplesWe will load a model of the Franka-Emika Panda robot defined by a URDF fileimportroboticstoolboxasrtbrobot=rtb.models.Panda()print(robot)ERobot:panda(byFrankaEmika),7joints(RRRRRRR),1gripper,geometry,collision┌─────┬──────────────┬───────┬─────────────┬────────────────────────────────────────────────┐│link│link│joint│parent│ETS:parenttolink│├─────┼──────────────┼───────┼─────────────┼────────────────────────────────────────────────┤│0│panda_link0││BASE│││1│panda_link1│0│panda_link0│SE3(0,0,0.333)⊕Rz(q0)││2│panda_link2│1│panda_link1│SE3(-90°,-0°,0°)⊕Rz(q1)││3│panda_link3│2│panda_link2│SE3(0,-0.316,0;90°,-0°,0°)⊕Rz(q2)││4│panda_link4│3│panda_link3│SE3(0.0825,0,0;90°,-0°,0°)⊕Rz(q3)││5│panda_link5│4│panda_link4│SE3(-0.0825,0.384,0;-90°,-0°,0°)⊕Rz(q4)││6│panda_link6│5│panda_link5│SE3(90°,-0°,0°)⊕Rz(q5)││7│panda_link7│6│panda_link6│SE3(0.088,0,0;90°,-0°,0°)⊕Rz(q6)││8│@panda_link8││panda_link7│SE3(0,0,0.107)│└─────┴──────────────┴───────┴─────────────┴────────────────────────────────────────────────┘┌─────┬─────┬────────┬─────┬───────┬─────┬───────┬──────┐│name│q0│q1│q2│q3│q4│q5│q6│├─────┼─────┼────────┼─────┼───────┼─────┼───────┼──────┤│qr│0°│-17.2°│0°│-126°│0°│115°│45°││qz│0°│0°│0°│0°│0°│0°│0°│└─────┴─────┴────────┴─────┴───────┴─────┴───────┴──────┘The symbol@indicates the link as an end-effector, a leaf node in the rigid-body
tree (Python prompts are not shown to make it easy to copy+paste the code, console output is indented).
We will compute the forward kinematics nextTe = robot.fkine(robot.qr)  # forward kinematics
print(Te)

	0.995     0         0.09983   0.484
	0        -1         0         0
	0.09983   0        -0.995     0.4126
	0         0         0         1We can solve inverse kinematics very easily. We first choose an SE(3) pose
defined in terms of position and orientation (end-effector z-axis down (A=-Z) and finger
orientation parallel to y-axis (O=+Y)).fromspatialmathimportSE3Tep=SE3.Trans(0.6,-0.3,0.1)*SE3.OA([0,1,0],[0,0,-1])sol=robot.ik_lm_chan(Tep)# solve IKprint(sol)(array([0.20592815,0.86609481,-0.79473206,-1.68254794,0.74872915,2.21764746,-0.10255606]),1,114,7,2.890164057230228e-07)q_pickup=sol[0]print(robot.fkine(q_pickup))# FK shows that desired end-effector pose was achieved1-8.913e-05-0.00033340.5996-8.929e-05-1-0.0004912-0.2998-0.00033340.0004912-10.10010001We can animate a path from the ready poseqrconfiguration to this pickup configurationqt=rtb.jtraj(robot.qr,q_pickup,50)robot.plot(qt.q,backend='pyplot',movie='panda1.gif')where we have specified the matplotlibpyplotbackend. Blue arrows show the joint axes and the coloured frame shows the end-effector pose.We can also plot the trajectory in the Swift simulator (a browser-based 3d-simulation environment built to work with the Toolbox)robot.plot(qt.q)We can also experiment with velocity controllers in Swift. Here is a resolved-rate motion control exampleimportswiftimportroboticstoolboxasrpimportspatialmathassmimportnumpyasnpenv=swift.Swift()env.launch(realtime=True)panda=rp.models.Panda()panda.q=panda.qrTep=panda.fkine(panda.q)*sm.SE3.Trans(0.2,0.2,0.45)arrived=Falseenv.add(panda)dt=0.05whilenotarrived:v,arrived=rp.p_servo(panda.fkine(panda.q),Tep,1)panda.qd=np.linalg.pinv(panda.jacobe(panda.q))@venv.step(dt)# Uncomment to stop the browser tab from closing# env.hold()Run some examplesThenotebooksfolder contains some tutorial Jupyter notebooks which you can browse on GitHub. Additionally, have a look in theexamplesfolder for many ready to run examples.Toolbox Research ApplicationsThe 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.Publication ListJ. Haviland, N. Sünderhauf and P. Corke, "A Holistic Approach to Reactive Mobile Manipulation," inIEEE 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 theSwiftSimulator.[Arxiv Paper] [IEEE Xplore] [Project Website] [Video] [Code Example]J. Haviland and P. Corke, "NEO: A Novel Expeditious Optimisation Algorithm for Reactive Motion Control of Manipulators," inIEEE Robotics and Automation Letters, doi: 10.1109/LRA.2021.3056060. In the video, the robot is controlled using the Robotics toolbox for Python and features a recording from theSwiftSimulator.[Arxiv Paper] [IEEE Xplore] [Project Website] [Video] [Code Example]A Purely-Reactive Manipulability-Maximising Motion Controller, J. Haviland and P. Corke. In the video, the robot is controlled using the Robotics toolbox for Python.[Paper] [Project Website] [Video] [Code Example]Toolbox ICRA Paper and Citation InfoCheck out our ICRA 2021 paper onIEEE Xploreor get the PDF fromPeter's website.If the toolbox helped you in your research, please cite@inproceedings{rtb,
  title={Not your grandmother’s toolbox--the Robotics Toolbox reinvented for Python},
  author={Corke, Peter and Haviland, Jesse},
  booktitle={2021 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={11357--11363},
  year={2021},
  organization={IEEE}
}Using the Toolbox in your Open Source Code?If you are using the Toolbox in your open source code, feel free to add our badge to your readme!For the powered by robotics toolbox badgecopy the following[![Powered by the Robotics Toolbox](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/rtb_powered.min.svg)](https://github.com/petercorke/robotics-toolbox-python)For the powered by python robotics badgecopy the following[![Powered by Python Robotics](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/pr_powered.min.svg)](https://github.com/petercorke/robotics-toolbox-python)Common Issues and SolutionsSee the common issues with fixeshere.