Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908524748996608 |
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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 |