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A python based light weight robot simulator for the intelligent robotics navigation and learning

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Intelligent Robot Simulator (IR-SIM)

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IR-SIM is an open-source, lightweight robot simulator based on Python, specifically designed for intelligent robotics navigation and learning. Primarily intended for research and educational purposes, it is user-friendly and easily customizable.

It provides the following features:

  • A versatile and easy-to-use framework for simulating a variety of robot platforms with kinematics and sensors.
  • Customizable configurations and parameters using yaml files.
  • Real-time visualization of simulation outcomes.
  • Ideal for developing and testing algorithms related to robot navigation, motion planning, reinforcement learning.
Robot Car
robot car

Prerequisite

  • Python: >= 3.7

Installation

  • Install this package from PyPi:
pip install ir-sim
  • Or for development, you may install from source:
git clone https://github.com/hanruihua/ir-sim.git    
cd ir-sim   
pip install -e .  

Usage

Quick Start

import irsim

env = irsim.make('robot_world.yaml') # initialize the environment with the configuration file

for i in range(300): # run the simulation for 300 steps

    env.step()  # update the environment
    env.render() # render the environment

    if env.done(): break # check if the simulation is done
        
env.end() # close the environment

YAML Configuration: robot_world.yaml

world:
  height: 10  # the height of the world
  width: 10   # the height of the world
  step_time: 0.1  # 10Hz calculate each step
  sample_time: 0.1  # 10 Hz for render and data extraction 
  offset: [0, 0] # the offset of the world on x and y 

robot:
  kinematics: {name: 'diff'}  # omni, diff, acker
  shape: {name: 'circle', radius: 0.2}  # radius
  state: [1, 1, 0]  # x, y, theta
  goal: [9, 9, 0]  # x, y, theta
  behavior: {name: 'dash'} # move toward to the goal directly 
  color: 'g' # green

Advanced Usage

The advanced usages are listed in the irsim/usage

Cases

Acknowledgement