Welcome to BiguaSim’s documentation!

BiguaSim is a high-fidelity simulator developed by Nautec at Federal University of Rio Grande .

Features

  1. Multi-Domain Simulation Environments: Rich, high-fidelity worlds supporting simultaneous operations of both air and water vehicles (UAVs and AUVs).

  2. Powered by Unreal Engine 5 (UE5): Leverages modern UE5 rendering and physics for maximum visual realism and high-detail environments.

  3. Synthetic Dataset Generation: Purpose-built infrastructure for generating realistic, annotated synthetic data to train perception and AI models.

  4. Comprehensive Sensor Suite: Complete with common multi-domain sensors including DVL, IMU, optical cameras, high-precision depth cameras, and more, customized for both aerial and underwater domains.

  5. Advanced Hybrid Sonar Framework: Novel simulation framework for imaging, profiling, sidescan, and singlebeam sonars, featuring simultaneous Ground Truth (GT) extraction and realistic stochastic noise modeling.

  6. Sim-2-Real Focus: Realistic sensor noise and physics modeling designed to minimize the sim-to-real gap for seamless algorithm deployment.

  7. Multi-Agent Missions: Easily configure and scale complex multi-robot missions.

  8. OpenAI Gym-like Python Interface: Simple installation and intuitive API for testing robotics algorithms and training Reinforcement Learning agents.

  9. High Performance & Flexibility: Configurable execution speeds. Run visually or in headless mode. Pay a computational penalty only for the features you need.

  10. Cross-Platform: Full support for Linux and Windows.

Attribution and Relevent Publications

If you use BiguaSim in your research, please cite the following publication:

General BiguaSim use:

@inproceedings{11338720,
   author={Mateus, Matheus G. and De Oliveira, Guilherme C. and Reichow, Luis Henrique K. and Kolling, Alisson H. and Pinheiro, Pedro M. and Drews-Jr, Paulo L. J.},
   booktitle={2025 IEEE International Conference on Advanced Robotics (ICAR)},
   title={BiguaSim: A Hybrid Multi-Domain Simulator for Robotics High-Fidelity Simulation and Synthetic Dataset Generation},
   year={2025},
   volume={},
   number={},
   pages={169-174},
   keywords={Data collection;Robot sensing systems;Hybrid power systems;Complexity theory;Vehicle dynamics;Engines;Testing;Synthetic data},
   doi={10.1109/ICAR65334.2025.11338720}
}

BiguaSim Documentation

API Documentation

Indices and tables