pykin

Python Interface for the robot Kinematics library pykin

This library has been created simply by referring to ikpy.

Features

Pure python library
Support only URDF file
Compute forward, inverse kinematics and jacobian, referred to the Introduction to Humanoid Robotics book.
Check robot self-collision and collision between objects
Plot robot kinematic chain and mesh

Installation

Requirements

You need a python-fcl package to do object collision checking.

For Ubuntu, using apt

sudo apt install liboctomap-dev

sudo apt install libfcl-dev
For Mac, First, Download the source and build it.
- octomap
  
  git clone https://github.com/OctoMap/octomap.git
```
$ cd octomap
$ mkdir build
$ cd build
$ cmake ..
$ sudo make
$ sudo make install
```
- fcl
  
  git clone https://github.com/flexible-collision-library/fcl.git
  
  Since python-fcl uses version 0.5.0 of fcl, checkout with tag 0.5.0
```
$ cd fcl
$ git checkout 0.5.0
$ mkdir build
$ cd build
$ cmake ..
$ sudo make
$ sudo make install
```

Install Pykin

pip3 install pykin

Quick Start

You can see various examples in examples directory

Robot Info

You can see 7 robot info.

baxter, sawyer, iiwa14, iiwa7, panda, ur5e, doosan

$ cd examples
$ python robot_info.py $(robot_name)
# baxter
$ python robot_info.py baxter
# saywer
$ python robot_info.py sawyer

Forward kinematics

You can compute the forward kinematics as well as visualize the visual or collision geometry.
```
$ cd examples/forward_kinematics
$ python robot_fk_baxter_test.py
```
visual collision
Inverse Kinematics

You can compute the inverse kinematics using levenberg marquardt(LM) or newton raphson(NR) method
```
$ cd examples/inverse_kinematics
$ python robot_ik_baxter_test.py
```
Sampling based Inverse Kinematics

You can compute the inverse kinematics using geometric-aware bayesian optimization(GaBO) method

For more detailed information, check GaBO module
```
$ cd examples/inverse_kinematics
$ python robot_ik_gabo_test.py
```
Collision check

The below images show the collision result as well as visualize robot using trimesh.Scene class
```
$ cd examples/trimesh_renders
$ python sawyer_render.py
```
trimesh.Scene Result

Visualization

You can see visualization using matplotlib library or trimesh.Scene class.

Visualize simple urdf using matplotlib

ur5e sawyer iiwa14 panda
Visualize visual geometry using matplotlib

ur5e sawyer iiwa14 panda
Visualize collision geometry using matplotlib

ur5e sawyer iiwa14 panda
Visualize mesh about visual/collision geometry using trimesh.Scene class

Metadata

Release files for pykin 1.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pykin 1.6.0
File	Size	Uploaded	Provenance
pykin-1.6.0.tar.gz	50.7 MB	Jan 26, 2023	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for pykin 1.6.0
File	Interpreter	ABI	Platform	Reset
pykin-1.6.0-py3-none-any.whl 50.8 MB Jan 26, 2023 Without provenance	Python 3	none	any	Details

Total release size: 101.5 MB

Release files / pykin-1.6.0.tar.gz

Download URL	pykin-1.6.0.tar.gz
Size	50.7 MB
Tags	Source
SHA-256 checksum How to use checksums	`a8f6af2a281be933e386aa0cd8783f61144500fdcdeb81121377a981a51b9677`
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Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.1.1 pkginfo/1.4.2 requests/2.28.1 setuptools/60.2.0 requests-toolbelt/0.8.0 tqdm/4.64.1 CPython/3.8.10`

Release files / pykin-1.6.0-py3-none-any.whl

Download URL	pykin-1.6.0-py3-none-any.whl
Size	50.8 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`54f52c3be6c123eab6771810908e9e43b68b2e23af4ca4efe9790445f80f8481`
BLAKE2b-256 checksum How to use checksums	`f87c1c779dcbb965ea4a18ec8d53d89ef1b289463866673ace6262e1751e1abc`
Upload date	Jan 26, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.1.1 pkginfo/1.4.2 requests/2.28.1 setuptools/60.2.0 requests-toolbelt/0.8.0 tqdm/4.64.1 CPython/3.8.10`

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