Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data

arXiv:2505.15465 · cs.RO · Submitted 2025-05-21 · Read on arXiv

cs.RO

Submitted: 2025-05-21

Updated: 2026-09-23

Code: https://github.com/guilhermecdo/SEE

Terminology

• Synthetic Enclosed Echoes — 7× in this paper
• Fidelity — 4× in this paper · explained in 2 episodes
• Self-Supervised Learning — 4× in this paper · explained in 7 episodes
• Aperture — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Hybrid Approach — 2× in this paper · explained in 4 episodes
• Point Clouds — 2× in this paper · explained in 2 episodes
• ROOT MEAN SQUARE — 2× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Computer-Aided Design — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• U-net architecture — 1× in this paper · explained in 3 episodes

Sources

• Depth Anything V2
• Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
• Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving