IR-SIM is an open-source, lightweight robot 2D 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 |
|---|---|
 |
 |
- Python: >= 3.7
- 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 .
from ir_sim.env import EnvBase
env = EnvBase('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 environmentYAML 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' # greenThe advanced usages are listed in the ir_sim/usage
- rl-rvo-nav(RAL & ICRA2023)
- RDA_planner（RAL & IROS2023）