A RoboStack Tutorial: Using the Robot Operating System Alongside the Conda and Jupyter Data Science Ecosystems

TL;DR

This paper introduces RoboStack, a framework that integrates Robot Operating System with Conda and Jupyter, enabling seamless data science and robotics workflows across multiple platforms and ROS versions.

Contribution

It provides new Conda packages for ROS, improves installation speed, and offers JupyterLab extensions for robotics, facilitating combined data science and robotics development.

Findings

Multiple ROS versions can run simultaneously on one machine.

ROS packages are now easily installable via Conda across platforms.

Enhanced speed of the Conda solver and build system for large ecosystems.

Abstract

We argue that it is beneficial to tightly couple the widely-used Robot Operating System with Conda, a cross-platform, language-agnostic package manager, and Jupyter, a web-based interactive computational environment affording scientific computing. We provide new ROS packages for Conda, enabling the installation of ROS alongside data-science and machine-learning packages with ease. Multiple ROS versions (currently ROS1 Melodic and Noetic, as well as ROS2 Foxy and Galactic) can run simultaneously on one machine, with pre-compiled binaries available for Linux, Windows and OSX, and the ARM architecture (e.g. the Raspberry Pi and the new Apple Silicon). To deal with the large size of the ROS ecosystem, we significantly improved the speed of the Conda solver and build system by rewriting the crucial parts in C++. We further contribute a collection of JupyterLab extensions for ROS, including plugins for live plotting, debugging and robot control, as well as tight integration with Zethus, an RViz like visualization tool. Taken together, RoboStack combines the best of the data-science and robotics worlds to help researchers and developers to build custom solutions for their academic and industrial projects.