Multimodal Trajectory Planning for Surface Vehicles using Turning Circle-based Control Barrier Functions
arXiv:2608.19537v1 Announce Type: new Abstract: This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The proposed method integrates model predictive control (MPC) with a turning circle-based control barrier function (TC-CBF). Unlike conventional Euclidean distance-based CBFs (ED-CBFs), which evaluate safety solely based on proximity, the TC-CBF accounts for the nonholonomic motion and finite turning capability of a surface vehicle. Its geometric formulation identifies feasible avoidance regions according to the vehicle's turning circles and generates distinct left- and right-turning avoidance modes. These modes allow the optimization solver to explore and select topologically different trajectories without relying on globally planned guide paths, as required by many conventional multimodal planning approaches. By embedding the avoidance direction directly into the safety constraint, the proposed framework alleviates the local-minimum and deadlock problems of single-mode MPC while maintaining computational efficiency. Extensive simulations involving multiple moving vessels demonstrate that the proposed method achieves higher success rates, fewer safety violations, and smaller residual violations than single-mode baselines across all tested traffic densities.
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[Submitted on 20 Aug 2026]
Title:Multimodal Trajectory Planning for Surface Vehicles using Turning Circle-based Control Barrier Functions
View a PDF of the paper titled Multimodal Trajectory Planning for Surface Vehicles using Turning Circle-based Control Barrier Functions, by Changyu Lee
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Abstract:This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The proposed method integrates model predictive control (MPC) with a turning circle-based control barrier function (TC-CBF). Unlike conventional Euclidean distance-based CBFs (ED-CBFs), which evaluate safety solely based on proximity, the TC-CBF accounts for the nonholonomic motion and finite turning capability of a surface vehicle. Its geometric formulation identifies feasible avoidance regions according to the vehicle's turning circles and generates distinct left- and right-turning avoidance modes. These modes allow the optimization solver to explore and select topologically different trajectories without relying on globally planned guide paths, as required by many conventional multimodal planning approaches. By embedding the avoidance direction directly into the safety constraint, the proposed framework alleviates the local-minimum and deadlock problems of single-mode MPC while maintaining computational efficiency. Extensive simulations involving multiple moving vessels demonstrate that the proposed method achieves higher success rates, fewer safety violations, and smaller residual violations than single-mode baselines across all tested traffic densities.
Comments: This work has been submitted to an Elsevier journal for possible publication
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2608.19537 [cs.RO]
(or arXiv:2608.19537v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.19537
arXiv-issued DOI via DataCite (pending registration)
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From: Changyu Lee [view email] [v1] Thu, 20 Aug 2026 01:18:07 UTC (2,564 KB)
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