pink_bench

A library of robot motions performed by inverse kinematics and model predictive control.

Installation

For best compatibility we recommended installing the bench from Conda:

conda install -c conda-forge pink_bench

You can also install it from PyPI:

pip install pink_bench

To play a scenario from the library, simply call:

pink_bench.play_scenario(
    name="jaxon",
    dt=0.005,  # seconds
    qpsolver="proxqp",
)

This will open a MeshCat tab in your web browser playing the scenario for its prescribed duration. You can also do the same from the command-line:

$ ./examples/run_scenario.py jaxon --dt 0.005 --qpsolver proxqp

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

Source distribution for pink_bench 0.2.0
File	Size	Uploaded
pink_bench-0.2.0.tar.gz	18.2 kB	Dec 16, 2024	Details

Table of built distributions (wheels) for pink_bench 0.2.0
File	Interpreter	ABI	Platform	Reset
pink_bench-0.2.0-py3-none-any.whl 21.1 kB Dec 16, 2024	Python 3	none	any	Details

Total release size: 39.3 kB

Download URL	pink_bench-0.2.0.tar.gz
Size	18.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`7ce4a4e46b209e3927cfb8e08b88302f14f03f3d8a23985b7b06e6ee6f5aa23a`
BLAKE2b-256 checksum How to use checksums	`aa125c86e69af0457d29b2b337cc0682c315f3ca17dcb1b6e54092ff2a00a427`
Upload date	Dec 16, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`python-requests/2.31.0`

Download URL	pink_bench-0.2.0-py3-none-any.whl
Size	21.1 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`1e0807decc000d775b4da08fd30c5e5a327e0e62575a4ddcb9df0c3b3db3f9ec`
BLAKE2b-256 checksum How to use checksums	`4e85a3be05194ca710d3d8f7f6332b2db9edbcc969b5135f78b32b5df65d6387`
Upload date	Dec 16, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`python-requests/2.31.0`