Metadata-Version: 2.1
Name: qibullet
Version: 1.4.5
Summary: Bullet-based simulation for SoftBank Robotics' robots
Home-page: https://github.com/softbankrobotics-research/qibullet
Author: Maxime Busy, Maxime Caniot
Author-email: 
License: UNKNOWN
Keywords: physics simulation,robotics,naoqi,softbank,pepper,nao,romeo,robot
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft
Classifier: Topic :: Games/Entertainment :: Simulation
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Framework :: Robot Framework :: Tool
Description-Content-Type: text/markdown
License-File: LICENSE

# qiBullet [![ci](https://github.com/softbankrobotics-research/qibullet/workflows/ci/badge.svg?branch=master)](https://github.com/softbankrobotics-research/qibullet/actions?query=workflow%3Aci) [![codecov](https://codecov.io/gh/softbankrobotics-research/qibullet/branch/master/graph/badge.svg)](https://codecov.io/gh/softbankrobotics-research/qibullet) [![pypi](https://img.shields.io/pypi/v/qibullet.svg)](https://pypi.org/project/qibullet/) [![Downloads](https://pepy.tech/badge/qibullet)](https://pepy.tech/project/qibullet) [![Github discussions](https://img.shields.io/github/discussions/softbankrobotics-research/qibullet?color=blue&logo=github)](https://github.com/softbankrobotics-research/qibullet/discussions) [![docs](https://img.shields.io/badge/docs-online-success?logo=githubpages)](https://softbankrobotics-research.github.io/qibullet/)

__Bullet-based__ python simulation for __SoftBank Robotics'__ robots.



## Installation

The following modules are required:
* __numpy__
* __pybullet__

The qiBullet module can be installed via pip, for python 2.7 and python 3:
```bash
pip install --user qibullet
```

Additional resources (robot meshes and URDFs) are required in order to be able to spawn a Pepper, NAO or Romeo robot in the simulation. These extra resources will be installed in your home folder:
* `/home/username/.qibullet` on Linux and macOS
* `C:\Users\username\.qibullet` on Windows

The installation of the additional resources will automatically be triggered if you try to spawn a Pepper, NAO or Romeo for the first time. If qiBullet finds the additional resources in your local folder, the installation won't be triggered. The robot meshes are under a specific [license](https://github.com/softbankrobotics-research/qibullet/tree/master/qibullet/robot_data/LICENSE), you will need to agree to that license in order to install them. More details on the installation process can be found on the [wiki](https://github.com/softbankrobotics-research/qibullet/wiki).

## Usage
A robot can be spawned via the SimulationManager class:
```python
import sys
from qibullet import SimulationManager

if __name__ == "__main__":
    simulation_manager = SimulationManager()

    # Launch a simulation instances, with using a graphical interface.
    # Please note that only one graphical interface can be launched at a time
    client_id = simulation_manager.launchSimulation(gui=True)

    # Selection of the robot type to spawn (True : Pepper, False : NAO)
    pepper_robot = True

    if pepper_robot:
      # Spawning a virtual Pepper robot, at the origin of the WORLD frame, and a
      # ground plane
      pepper = simulation_manager.spawnPepper(
          client_id,
          translation=[0, 0, 0],
          quaternion=[0, 0, 0, 1],
          spawn_ground_plane=True)
    else:
      # Or a NAO robot, at a default position
      nao = simulation_manager.spawnNao(
          client_id,
          spawn_ground_plane=True)

    # This snippet is a blocking call, just to keep the simulation opened
    if sys.version_info[0] >= 3:
      input("Press a key to end the simulation")
    else:
      raw_input("Press a key to end the simulation")
    
    # Stop the simulation
    simulation_manager.stopSimulation(client_id)
    
```

Or using loadRobot from the PepperVirtual class if you already have a simulated environment:
```python
    pepper = PepperVirtual()

    pepper.loadRobot(
      translation=[0, 0, 0],
      quaternion=[0, 0, 0, 1],
      physicsClientId=client_id)
```

More snippets can be found in the [examples folder](https://github.com/softbankrobotics-research/qibullet/tree/master/examples), or on the [wiki](https://github.com/softbankrobotics-research/qibullet/wiki)

> :warning: The camera subscription system of qiBullet 1.4.0 (and lesser) is __deprecated__, use the [new system](https://github.com/softbankrobotics-research/qibullet/wiki/Tutorials:-Virtual-Robot#cameras)

## Documentation
The qiBullet __API documentation__ can be found [here](https://softbankrobotics-research.github.io/qibullet/). In order to build the documentation, the __doxygen__ package has to be installed beforehand and the docs folder has to exist. The submodules should also be checked out:
```bash
git submodule init
git submodule update
```

The documentation can then be generated via the following command:
```bash
cd docs
doxygen Doxyfile
```

The repository also contains a [wiki](https://github.com/softbankrobotics-research/qibullet/wiki), providing some tutorials.

## Citations
Please cite qiBullet if you use this repository in your publications:
```
@article{busy2019qibullet,
  title={qiBullet, a Bullet-based simulator for the Pepper and NAO robots},
  author={Busy, Maxime and Caniot, Maxime},
  journal={arXiv preprint arXiv:1909.00779},
  year={2019}
}
```

## Troubleshooting

### OpenGL driver
If you encounter the message:
> Workaround for some crash in the Intel OpenGL driver on Linux/Ubuntu

Your computer is using the Intel OpenGL driver. Go to __Software & Updates__, __Additional Drivers__, and select a driver corresponding to your GPU.

## License
Licensed under the [Apache-2.0 License](LICENSE)


