Here you will find several examples of robots that were design to be exported properly using the onshape-to-robot tool.
Have a look at the design-time considerations to understand better the constraints to export your robots to URDF/SDF.
Before testing, in a nutshell, you need onshape-to-robot
:
pip install onshape-to-robot
This repository contains both config.json
file and resulting URDF, SDF and STL files. Thus, they can seen in a
physics environment easily using:
onshape-to-robot-bullet [directory]
This will open a windows like the following one, including sliders to change the degree of freedom positions:
Description: Very simple design and minimalistic configuration
- Give it a try:
onshape-to-robot-bullet 2wheels
- Onshape design
- config.json
- Note: joints names ends with
_speed
, which makesonshape-to-robot
use speed control by default - Note2: here,
wheel2
has the_inv
suffix, which changes its direction making both wheels spin in same direction when same sign of order is given
Description: Robot with 4 degrees of freedom, one prismatic (linear) joint and 3 rotations
- Give it a try:
onshape-to-robot-bullet -f adjustable_height_arm
(note that-f
is passed to fix the base to the ground) - Onshape design
- config.json
- There is one frame (
frame_tip
) attached to the tip of the arm
Description: Example of (not implemented) omnidirectional robot using omni wheels (holonomic)
- Give it a try:
onshape-to-robot-bullet omnidirectional
- Onshape design
- config.json
- Each small wheel is a degree of freedom. This is not very hard to do, even though a little tedious.
- There is a frame (
frame_body
) in the very center of the robot. A visual arrow is part of the plate to indicate the front (axis X) of the robot.
Description: 12 DOF quadruped robot, design similar to the Metabot open-source project using XL-320 servos.
- Give it a try:
onshape-to-robot-bullet quadruped
- Onshape design
- config.json
- Full pure shape approximation (OpenSCAD) for collisions
- Frames in the trunk (
trunk_frame
) and in the tip of one leg (tip_frame
)
Description: 12 DOF dog robot, made for fun with MX-64 servos (was actually built)
- Give it a try:
onshape-to-robot-bullet dog
- Onshape design
- config.json
- No pure shape approximation (pure STLs)
- Dynamics is overridden for MX-64 and MX-106, since it is provided by constructor
Description: 20 DOF humanoid robot, snapshot of 2019 Sigmaban model from team [Rhoban][https://www.youtube.com/watch?v=tF0cr0PYjsk), used at RoboCup kid size
- Give it a try:
onshape-to-robot-bullet sigmaban2019
- Onshape design
- config.json
- Full pure shape approximation (OpenSCAD) for collisions
- Dynamics is overridden for [MX-64][http://emanual.robotis.com/docs/en/dxl/mx/mx-64-2/) and MX-106, since it is provided by constructor
- Pure shapes are rendered for speed, you can set
drawCollisions
do false and re-run import to have real meshes visual- (To lighten the repository, meshes were not committed)
- Frames in the trunk (
trunk_frame
), in feet (right_foot_frame
,left_foot_frame
), the camera (camera_frame), the head base (
head_base_frame) and some location to use Vive tracker for ground-truth (
vive_frame`).
Description: This is not actually a robot, but an environment that is designed in Onshape and can be converted into an URDF file
- Give it a try:
onshape-to-robot-bullet field
- Onshape design
- config.json
- Note that the
noDynamics
is set totrue
in the configuration, making it a static environment - This is a model of RoboCup humanoid soccer kid-size (2019) 6 x 9 m field
- The
useFixedLinks
option is set totrue
so that the colors of different sub-part are kept
Read the instructions from the onshape-to-robot repository, especially
be sure to have the API key registered and set as environment variable before running onshape-to-robot
.
To get the same results, you might need openscad
and meshlab
installed.
sudo apt-get install openscad meshlab
Else, pure shape approximation and meshes simplification might be disabled.
If you want to export the robots yourself, you need to have the rights to access to the assembly. Thus, if you want to re-run the import for the examples in this repository, you will have to make your own copy of the document. Fortunately, this is quite simple because it is just about clicking on that button on top left:
Then, change the documentId
in config.json
of the robot to match the new document created where you own the robot
design.
Actually, pyBullet does only keep one color per link currently in the viewer. This is a known limitation that does not affect your physical simulations. (bulletphysics/bullet3#2650)
For instance, the quadruped robot above will look like this: