Skip to main content

An AR controller designed to seamlessly control objects in MuJoCo and for other general uses by receiving position and rotation data from a connected iOS application.

Project description

Logo  MuJoCo AR

PyPI version License: MIT

MuJoCo AR is a plugin for MuJoCo that enables the integration of ARKit data from a connected iOS device to control MuJoCo frames in real-time. It can also be used in non-MuJoCo applications (see the flexible setup section below). This package accompanies the MuJoCo AR iOS app that can be downloaded from here.

Demos

Position Control
MuJoCo Fruits Pick and Place MuJoCo PushT
Position and Rotation Control
MuJoCo Study Desk MuJoCo Blocks Stacking

Examples of MuJoCo AR linked to the end-effectors of multiple manipulators can be found in this fork of Mink. For a simpler environemnt that the ones shwon in the demo section above, check the example at demo/simple_example.py

Installation

  1. iOS App: Download the iOS app from the App Store here

  2. Python Package: Install the Python package using pip:

pip install mujoco_ar

Usage

Quick MuJoCo Setup

This setup allows you to directly control a MuJoCo frame (body, geom, or site), with the frame's position and orientation matching the ARKit data received from the connected iOS device.

from mujoco_ar import MujocoARConnector

# Initialize the connector with your desired parameters
mj_ar = MujocoARConnector(mujoco_model=my_model,mujoco_data=my_data)

# Link a MuJoCo frame (link_body(), link_geom() or link_site())
mj_ar.link_body(name="eef_target")

# Start the connector
mj_ar.start()

Full MuJoCo Setup

In addition to what the quick setup allows you to do, this setup allows you to automate the applying of a translation, rotation or scaling of the recieved pose. Additionally, you can pass functions to button_fn and toggle_fn to be triggered when the button or toggle are activated

from mujoco_ar import MujocoARConnector

# Initialize the connector with your desired parameters
mj_ar = MujocoARConnector(
    mujoco_model=my_model, 
    mujoco_data=my_data, 
    port=8888,                                           # Optional, defaults to 8888 if not provided
    debug=False                                          # Optional, defaults to False if not provided
)

# Link a MuJoCo frame (link_body(), link_geom() or link_site())
mj_ar.link_body(
    name="eef_target",
    scale=1.0,                                           # Optional, defaults to 1.0 if not provided
    position_origin=np.array([0.0, 0.0, 0.0]),           # Optional, defaults to [0, 0, 0] if not provided
    rotation_origin=np.identity(3),                      # Optional, defaults to I(3) if not provided
    toggle_fn=my_toggle_function,                        # Optional, calls nothing if not provided
    button_fn=my_button_function,                        # Optional, calls nothing if not provided
    disable_pos=False,                                   # Optional, defaults to False if not provided
    disable_rot=False                                    # Optional, defaults to False if not provided
)

# Start the connector
mj_ar.start()

Flexible Setup (works without MuJoCo):

You can retrieve the ARKit data including the position, rotation, button, and toggle states directly from a connected iOS device, making it flexible for usage in various applications beyond physics simulations.

from mujoco_ar import MujocoARConnector

# Initialize the connector with your desired parameters
connector = MujocoARConnector()

# Start the connector
connector.start()

# Retrieve the latest AR data (after connecting the iOS device, see the guide below)
data = connector.get_latest_data()  # Returns {"position": (3, 1), "rotation": (3, 3), "button": bool, "toggle": bool}

Additional Functions

connector.pause_updates()  # Temporarily stops receiving updates from the connected device.
connector.resume_updates() # Resumes receiving updates from the connected device.
connector.reset_position() # Resets the current position as the origin (0,0,0).

Acknowledgement

Thanks to @kevinzakka for the mink and mjctrl libraries, which are used in the provided demos.

Author

Omar Rayyan (olr7742@nyu.edu)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mujoco_ar-1.0.3.tar.gz (8.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mujoco_ar-1.0.3-py3-none-any.whl (8.1 kB view details)

Uploaded Python 3

File details

Details for the file mujoco_ar-1.0.3.tar.gz.

File metadata

  • Download URL: mujoco_ar-1.0.3.tar.gz
  • Upload date:
  • Size: 8.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.2

File hashes

Hashes for mujoco_ar-1.0.3.tar.gz
Algorithm Hash digest
SHA256 f7ff5818e4aeee8b82125709abe3cf01d2bd7b1b3387fc2e3d5ce98ca35483bf
MD5 a2c529e0e40324057220961324fa6af3
BLAKE2b-256 a9448420ccb284fbc409a1cf86459c0813ce5f48752c04b45e44025d87052660

See more details on using hashes here.

File details

Details for the file mujoco_ar-1.0.3-py3-none-any.whl.

File metadata

  • Download URL: mujoco_ar-1.0.3-py3-none-any.whl
  • Upload date:
  • Size: 8.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.2

File hashes

Hashes for mujoco_ar-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 49f5bc2e31a4f2c2492c636903616062bbd2c9decea6a01b312e26b09a353848
MD5 ce3dfee42ee2a3746e9597f52438f902
BLAKE2b-256 a4c765e90c7895a849d0c8866b89150a7f0dc2911a21ad796e60b5088d390dea

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page