A growing interest in develo** autonomous surface vehicles (ASVs) has been witnessed
during the past two decades, including COLREGs-compliant navigation to ensure safe …

This paper develops a Deep Reinforcement Learning (DRL)-based approach for the
navigation and control of autonomous surface vessels (ASVs) on inland waterways, where …

In the context of digital twins and integration of physics-based models with machine learning
tools, this paper proposes a new methodology for model selection and parameter …

Parallel self-assembly is an efficient approach to accelerate the assembly process for
modular robots. However, these approaches cannot accommodate complicated …

In many intelligent transportation systems, predicting the future motion of heterogeneous
traffic participants is a fundamental but challenging task due to various factors …

Self-assembly enables multi-robot systems to merge diverse capabilities and accomplish
tasks beyond the reach of individual robots. Incorporating varied docking mechanisms …

Autonomous vessels potentially enhance safety and reliability of seaborne trade. To
facilitate the development of autonomous vessels, high-fidelity simulations are required to …

A key component for maintaining safety while navigating onboard a vessel, is to obtain and
maintain situational awareness. Situational awareness comprises perceiving where you are …

Autonomous vehicles are anticipated to be a widespread and well-adopted aspect of urban
infrastructure by the end of the decade. With research and development scaling up over the …

In this paper, we investigate the formation tracking guidance control issues of multiple
unmanned surface vessels system with a noncooperative target. The visual leader guided …