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Robot Library (Python)

License: MIT CI Documentation: Publish

A modular Python library for building robot applications. It provides components for motion control, sensors, communications, and indicators over MQTT.

Documentation: the full site is auto-built and deployed to GitHub Pages on pushes to the dev branch. Once enabled in the repo settings, it will be available at: https://pera-swarm.github.io/robot-library-python/.

Installation

You can install in a few ways:

  • Editable (development) install from a local checkout:

    pip install -e .

  • From source via Git (replace org/repo as appropriate):

This library requires paho-mqtt (declared in pyproject.toml) and Python 3.8+.

Quick Start

Create a virtual robot by subclassing robot.VirtualRobot, configure MQTT, and start the main loop:

from robot import MQTTSettings, VirtualRobot
from robot.interfaces import RobotState


class MyRobot(VirtualRobot):
    def loop(self):
        if self.state == RobotState.RUN:
            print("running...")
            # do work
            self.delay(1000)


# Configure MQTT broker connection
MQTTSettings.server = "localhost"
MQTTSettings.port = 1883
MQTTSettings.user_name = ""
MQTTSettings.password = ""
MQTTSettings.channel = "v1"

r = MyRobot(1, 0, 0, 90)
r.start()
r.run()  # or run in a separate thread

See examples/my_test_robot.py for a complete runnable example.

Core Concepts

  • Robot: base lifecycle (start/stop/reset/delay/loop) and MQTT subscription handling. See robot.Robot.
  • VirtualRobot: convenient virtual implementation; subclass and implement loop. See robot.VirtualRobot.
  • Motion: differential drive style controller for movement and rotation. See robot.MotionController.
  • Sensors: distance, color, and proximity, with non-blocking MQTT updates and blocking request/reply helpers.
  • Communication: simple and directed messaging channels to other robots or a controller.
  • Indicators: NeoPixel control via MQTT topics.

Usage Examples

Motion control:

from robot import MotionController

motion = MotionController()  # standalone stub coordinate for quick tests
motion.move(100, 100, duration=1000)   # forward 1s
motion.rotate_degree(120, 90)          # rotate 90 degrees at speed 120

Sensors (within a Robot subclass after setup() has run):

dist = self.dist_sensor.get_distance()
rgb  = self.color_sensor.get_color()          # RGBColorType
prox = self.proximity_sensor.get_proximity()  # ProximityReadingType

Communications:

self.simple_comm.send_message("hello swarm")
self.directed_comm.send_message_with_distance("to leader", distance=25)

Indicators:

self.neo_pixel.change_color(255, 128, 0)

Extending and Customizing

  • New behavior: subclass VirtualRobot and implement loop. Optionally override sensor_interrupt or communication_interrupt.
  • New sensors/indicators: follow the pattern in robot.sensors.* and robot.indicators.*, implementing handle_subscription and publishing/consuming your desired topics via RobotMqttClient.
  • Motion tuning: adjust robot.configs.robot_settings.RobotSettings constants (speed bounds, robot geometry) to match your platform.
  • MQTT setup: set fields on robot.configs.mqtt_settings.MQTTSettings before constructing robots.

Documentation

Sphinx documentation lives in docs/ and is auto-generated on pushes to dev via GitHub Actions, then deployed to GitHub Pages. To build locally:

pip install -r docs/requirements.txt
sphinx-apidoc -o docs/api src/robot
python -m sphinx -b html docs docs/_build/html
open docs/_build/html/index.html

Contributing

  • Run lint and tests: flake8 src tests and PYTHONPATH=src pytest
  • Example to run: python examples/my_test_robot.py