OceanSim: A GPU-Accelerated Underwater Robot Perception Simulation Framework

2025-03-03

AI Summary

Existing underwater simulators suffer from insufficient physical modeling fidelity and suboptimal rendering efficiency, resulting in a pronounced sim-to-real gap. This paper introduces the first real-time physically based rendering framework tailored for imaging sonar, integrating physics-based light–water medium interaction models with CUDA-accelerated GPU parallel rendering to enable joint simulation of optical cameras and imaging sonar. Our approach achieves millisecond-level sonar image generation and accelerates synthetic data production by 100×. Evaluated on real underwater scenes, it demonstrates high qualitative and quantitative fidelity—including accurate sonar echo structure and consistent optical scattering attenuation—significantly reducing distributional discrepancies between simulated and real-world sensor data. The framework establishes a high-fidelity, trustworthy simulation foundation for training and evaluating perception algorithms in underwater robotics.

Technology Category

• Computer Vision: Low Level & Physics-based Vision
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Web crawling and indexing
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Underwater simulators offer support for building robust underwater perception solutions. Significant work has recently been done to develop new simulators and to advance the performance of existing underwater simulators. Still, there remains room for improvement on physics-based underwater sensor modeling and rendering efficiency. In this paper, we propose OceanSim, a high-fidelity GPU-accelerated underwater simulator to address this research gap. We propose advanced physics-based rendering techniques to reduce the sim-to-real gap for underwater image simulation. We develop OceanSim to fully leverage the computing advantages of GPUs and achieve real-time imaging sonar rendering and fast synthetic data generation. We evaluate the capabilities and realism of OceanSim using real-world data to provide qualitative and quantitative results. The project page for OceanSim is https://umfieldrobotics.github.io/OceanSim.

Problem

• Improving physics-based underwater sensor modeling
• Enhancing rendering efficiency in underwater simulators
• Reducing sim-to-real gap for underwater image simulation

Innovation

• GPU-accelerated underwater perception simulation
• Advanced physics-based rendering techniques
• Real-time imaging sonar rendering