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hanruihua / repository
A Python-based lightweight robot simulator designed for navigation, control, and learning
A lightweight, YAML-driven robot simulator for navigation, control, and learning
IR-SIM is an open-source, Python-based, lightweight robot simulator designed for navigation, control, and learning. It provides a simple, user-friendly framework with built-in collision detection for modeling robots, sensors, and environments. Ideal for academic and educational use, IR-SIM enables rapid prototyping of robotics and learning algorithms in custom scenarios with minimal coding and hardware requirements.
Requires Python >= 3.10
pip install ir-sim
# Optional: keyboard control and all extras
pip install ir-sim[all]
git clone https://github.com/hanruihua/ir-sim.git
cd ir-sim
pip install -e .
git clone https://github.com/hanruihua/ir-sim.git
cd ir-sim
uv sync
A minimal example: a differential-drive robot navigates toward a goal using the built-in dash behavior.
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 width 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, omni_angular, 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
For more examples, see the usage directory and the documentation.
| Category | Features |
|---|---|
| Kinematics | Differential Drive mobile Robot · Omnidirectional mobile Robot · Omnidirectional with Angular control · Ackermann Steering mobile Robot |
| Sensors | 2D LiDAR · 2D FMCW LiDAR · FOV Detector |
| Geometries | Circle · Rectangle · Polygon · LineString · Binary Grid Map · Fog of Map |
| Behaviors | dash (move directly toward goal) · RVO (Reciprocal Velocity Obstacle) · ORCA (Optimal Reciprocal Collision Avoidance) · SFM (Social Force Model) |
If you find IR-SIM useful, please consider starring ⭐ this project and citing our paper:
@article{han2026ir,
title={IR-SIM: A Lightweight Skill-Native Simulator for Navigation, Learning, and Benchmarking},
author={Han, Ruihua and Wang, Shuai and Li, Chengyang and Gao, Rui and Wang, Xinyi and Liu, Zhe and Li, Guoliang and Lu, Yupu and Hao, Qi and Pan, Jia and Zhao, Hengshuang},
journal={arXiv preprint arXiv:2606.08729},
year={2026}
}
Contributions are welcome! Please see CONTRIBUTING.md for guidelines.
IR-SIM is released under the MIT License.
Selected from shared topics, language and repository description—not editorial ratings.
Yuxiao-Cao /
A Python-based simulation platform built on SUMO and TraCI for testing and evaluating game-theoretic planning-and-control agents in interactive autonomous-driving scenarios, with a focus on unsignalized intersection interactions.