roxbot 4.1.0

Pythonic robotics toolkit

ROXBOT - a Pythonic robotics toolkit

What is this?

Project roxbot is a handbook for robotcs developers. It is intended as a knowledge base, providing a series of examples, reusable library code and tips and tricks for building robotic systems. Common use case is an AGV, navigating with an RTK-GPS module.

Project roadmap

see roadmap discussion

Note: watch this repository to be notified about updates. (we don't do spammy mailing lists)

Quick start

• documentation
• read the blog
• join discussion
• join the project!

What about ROS?

Well, ROS2 has some nice concepts, but it can be complex and complicated. Besides, ROS is C++ centric, which makes it a bit old-fashioned. Another shortcoming is a large codebase that has not been widely tried and tested in real world applications.

Key principles

• KISS (keep it simple, stupid): - let's make robotics easier by reducing complexity.
• Less Code Equals Fewer Problems: - keep codebase small and portable. "Code is not an asset but a liability"
• Don't reinvent the wheel - leverage robust existing technologies. Think of asyncio, Docker etc.

Concepts

ROXBOT takes familiar ideas from ROS2 and makes them easier to use and more Python-friendly:

• Nodes: These are small, focused classes that perform specific tasks within the robotics application. For example, one Node might manage sensor data while another controls a motor.

• Interfaces: These are standardized formats that ensure consistent data exchange between Nodes. This makes it easy for different parts of your project to communicate and work together effectively.

• Subsystems: This term refers to a group of Nodes that work together to perform a broader function like motion control or data logging. These subsystems can be packaged into Docker containers for easy deployment and scaling.

• System: This is the complete set of subsystems working together as a whole, forming a fully functional robotic system. We manage these as a Docker stack to ensure they are robust and scalable.

Classes overview

images are found in docs/uml

run invoke uml to update.