ASVSim (AirSim for Surface Vehicles): A High-Fidelity Simulation Framework for Autonomous Surface Vehicle Research

arXiv cs.RO / 4/22/2026

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Key Points

ASVSim is an open-source simulation framework designed specifically for autonomous surface vehicle (USV) research in inland waterways and ports, targeting the need for realistic test environments.
The framework combines simulated vessel dynamics with marine sensor simulations (including radar and cameras) and can generate synthetic datasets for computer vision and reinforcement learning.
Built on Cosys-AirSim, ASVSim supports both traditional control methods and deep learning-based approaches, enabling broad research use cases.
The authors demonstrate its capabilities through experiments in waterway segmentation and autonomous navigation, showing its value for algorithm development and evaluation.
ASVSim is released under the MIT license, aiming to lower barriers for ocean engineering researchers working on autonomous navigation.

Abstract

The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport. These systems can improve operational efficiency and safety, which is especially relevant in the European Union, where initiatives such as the Green Deal are driving a shift towards increased use of inland waterways. At the same time, a shortage of qualified personnel is accelerating the adoption of autonomous solutions. However, there is a notable lack of open-source, high-fidelity simulation frameworks and datasets for developing and evaluating such solutions. To address these challenges, we introduce AirSim for Surface Vehicles (ASVSim), an open-source simulation framework specifically designed for autonomous shipping research in inland and port environments. The framework combines simulated vessel dynamics with marine sensor simulation capabilities, including radar and camera systems and supports the generation of synthetic datasets for training computer vision models and reinforcement learning (RL) agents. Built upon Cosys-AirSim, ASVSim provides a comprehensive platform for developing autonomous navigation algorithms and generating synthetic datasets. The simulator supports research of both traditional control methods and deep learning-based approaches. Through experiments in waterway segmentation and autonomous navigation, we demonstrate the capabilities of the simulator in these research areas. ASVSim is provided as an open-source project under the MIT license, making autonomous navigation research accessible to a larger part of the ocean engineering community. See https://github.com/BavoLesy/ASVSim.