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Underwater Robotic Simulators Review for Autonomous System Development

Sara Aldhaheri, Yang Hu, Yongchang Xie, Peng Wu, Dimitrios Kanoulas, Yuanchang Liu

TL;DR

The paper addresses the challenge of selecting suitable underwater robotic simulators by providing a structured, in-depth review of five open-source, ROS-compatible URSs (Stonefish, DAVE, HoloOcean, MARUS, UNav-Sim). It analyzes each platform across architecture, physics, sensing capabilities, and sim-to-real potential, and discusses broader issues in sim-to-real transfer, benchmarking, and standardization. Key contributions include a comparative evaluation, practical guidance for practitioners, and a discussion of ongoing challenges such as realism–computational cost trade-offs and the need for an open benchmarking standard. The findings highlight how higher-fidelity simulators improve perceptual and control testing but require advanced hardware and maintenance, while emphasizing the importance of standardization and robust validation to enable transferable, field-ready underwater robotic systems.

Abstract

The increasing complexity of underwater robotic systems has led to a surge in simulation platforms designed to support perception, planning, and control tasks in marine environments. However, selecting the most appropriate underwater robotic simulator (URS) remains a challenge due to wide variations in fidelity, extensibility, and task suitability. This paper presents a comprehensive review and comparative analysis of five state-of-the-art, ROS-compatible, open-source URSs: Stonefish, DAVE, HoloOcean, MARUS, and UNav-Sim. Each simulator is evaluated across multiple criteria including sensor fidelity, environmental realism, sim-to-real capabilities, and research impact. We evaluate them across architectural design, sensor and physics modeling, task capabilities, and research impact. Additionally, we discuss ongoing challenges in sim-to-real transfer and highlight the need for standardization and benchmarking in the field. Our findings aim to guide practitioners in selecting effective simulation environments and inform future development of more robust and transferable URSs.

Underwater Robotic Simulators Review for Autonomous System Development

TL;DR

The paper addresses the challenge of selecting suitable underwater robotic simulators by providing a structured, in-depth review of five open-source, ROS-compatible URSs (Stonefish, DAVE, HoloOcean, MARUS, UNav-Sim). It analyzes each platform across architecture, physics, sensing capabilities, and sim-to-real potential, and discusses broader issues in sim-to-real transfer, benchmarking, and standardization. Key contributions include a comparative evaluation, practical guidance for practitioners, and a discussion of ongoing challenges such as realism–computational cost trade-offs and the need for an open benchmarking standard. The findings highlight how higher-fidelity simulators improve perceptual and control testing but require advanced hardware and maintenance, while emphasizing the importance of standardization and robust validation to enable transferable, field-ready underwater robotic systems.

Abstract

The increasing complexity of underwater robotic systems has led to a surge in simulation platforms designed to support perception, planning, and control tasks in marine environments. However, selecting the most appropriate underwater robotic simulator (URS) remains a challenge due to wide variations in fidelity, extensibility, and task suitability. This paper presents a comprehensive review and comparative analysis of five state-of-the-art, ROS-compatible, open-source URSs: Stonefish, DAVE, HoloOcean, MARUS, and UNav-Sim. Each simulator is evaluated across multiple criteria including sensor fidelity, environmental realism, sim-to-real capabilities, and research impact. We evaluate them across architectural design, sensor and physics modeling, task capabilities, and research impact. Additionally, we discuss ongoing challenges in sim-to-real transfer and highlight the need for standardization and benchmarking in the field. Our findings aim to guide practitioners in selecting effective simulation environments and inform future development of more robust and transferable URSs.

Paper Structure

This paper contains 22 sections, 2 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Underwater Robotic Simulation Overview
  3. Core modules of state-of-the-art URS
  4. Understanding the simulator framework
  5. Plugins / Extensions
  6. Physics Engine
  7. Visual Rendering or Graphics Engine
  8. Modeling the System
  9. Adding disturbances / noises (e.g., currents, waves, etc.)
  10. Key Criteria for Simulator Selection
  11. ROS Support
  12. Maintenance
  13. Open-source vs Proprietary
  14. Comparative Review of State-of-the-art Underwater Robotic Simulation
  15. Stonefish
  16. ...and 7 more sections

Figures (4)

  • Figure 1: State-of-the-art underwater robotic simulators.
  • Figure 2: Foundational framework for robotic simulators.
  • Figure 3: A timeline of URS (black), sim-to-real transfer frameworks (orange), and benchmarking tools (teal) released in recent years.
  • Figure 4: Research area distribution of publications that utilize the five reviewed simulator with the simulators' release years in parenthesis.