jyrobot

A lightweight Python robot simulator for Jupyter Lab, Notebooks, and other environments.

Goals

1. A lightweight mobile robotics simulator
2. Usable in the classroom, research, or exploration
3. Explore wheeled robots with range, cameras, and light sensors
4. Operate quickly without a huge amount of resources
5. Create reproducible experiments
6. Designed for exposition, experimentation, and analysis
7. Sensors designed for somewhat realistic problems (such as image recognition)
8. Especially designed to work easily with Machine Learning and Artificial Intelligence systems

Examples

There are pre-designed simulations ready to run, like this:

import jyrobot
import random

world = jyrobot.load("two-scribblers")

for robot in world.robots:
    # Give each robot a desired speed:
    robot.forward(1)

def control(world):
    for robot in world.robots:
        if robot.stalled:
	    # If stuck, just reverse:
            robot.reverse()
	# Turn randomly:
        robot.turn(1 - random.random() * 2)

# Watch the robots move in real time, or faster:
world.watch()
world.run(control, show=True, real_time=False)
# Press Control+C or interrupt the kernel to stop

You can also easily assemble your own simulations, robots, and sensors.

import jyrobot

world = jyrobot.World(width=100, height=100)
world.watch()

robot = jyrobot.Scribbler()

world.add_robot(robot)

robot.add_device(jyrobot.RangeSensor())
robot.add_device(jyrobot.Camera())

world.save_as("world-1")

Installation

For the core operations, you will need to install just jyrobot:

pip install jyrobot

For just image processing on top of of the core, you will need:

• Pillow - Python Image Library (PIL)

For the full set of options, you will need:

• Pillow - Python Image Library (PIL)
• ipywidgets
• IPython
• bqplot

There are three different backends:

• "pil" - requires Pillow (Python Image Library, PIL), the default; best tested
• "canvas" - requires ipycanvas and numpy; some issues
• "svg" - requires svgwrite and cairosvg (for backend.take_picture()); some issues

You can install all of the above with conda or pip.

To use the Jupyter enhancements, you'll also need the browser-based extensions. You can install those with:

jupyter labextension install @jupyter-widgets/jupyterlab-manager ipycanvas bqplot

If not in a conda environment, then you will also need to:

jupyter nbextension enable --py widgetsnbextension