Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways

Fuente: arXiv
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Autori principali: Ahmadi, Sajad, Esfahani, Hossein Nejatbakhsh, Velni, Javad Mohammadpour
Natura: Preprint
Pubblicazione: 2025
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author Ahmadi, Sajad
Esfahani, Hossein Nejatbakhsh
Velni, Javad Mohammadpour
author_facet Ahmadi, Sajad
Esfahani, Hossein Nejatbakhsh
Velni, Javad Mohammadpour
contents Deploying self-navigating surface vessels in inland waterways offers a sustainable alternative to reduce road traffic congestion and emissions. However, navigating confined waterways presents unique challenges, including narrow channels, higher traffic density, and hydrodynamic disturbances. Existing methods for autonomous vessel navigation often lack the robustness or precision required for such environments. This paper presents a new motion planning approach for Automated Surface Vessels (ASVs) using Robust Model Predictive Control (RMPC) combined with Control Barrier Functions (CBFs). By incorporating channel borders and obstacles as safety constraints within the control design framework, the proposed method ensures both collision avoidance and robust navigation on complex waterways. Simulation results demonstrate the efficacy of the proposed method in safely guiding ASVs under realistic conditions, highlighting its improved safety and adaptability compared to the state-of-the-art.
format Preprint
id arxiv_https___arxiv_org_abs_2509_06687
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
Ahmadi, Sajad
Esfahani, Hossein Nejatbakhsh
Velni, Javad Mohammadpour
Robotics
Systems and Control
Deploying self-navigating surface vessels in inland waterways offers a sustainable alternative to reduce road traffic congestion and emissions. However, navigating confined waterways presents unique challenges, including narrow channels, higher traffic density, and hydrodynamic disturbances. Existing methods for autonomous vessel navigation often lack the robustness or precision required for such environments. This paper presents a new motion planning approach for Automated Surface Vessels (ASVs) using Robust Model Predictive Control (RMPC) combined with Control Barrier Functions (CBFs). By incorporating channel borders and obstacles as safety constraints within the control design framework, the proposed method ensures both collision avoidance and robust navigation on complex waterways. Simulation results demonstrate the efficacy of the proposed method in safely guiding ASVs under realistic conditions, highlighting its improved safety and adaptability compared to the state-of-the-art.
title Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
topic Robotics
Systems and Control
url https://arxiv.org/abs/2509.06687