COLREGs-aware Trajectory Optimization for Autonomous Surface Vessels
A. Tsolakis (TU Delft - Learning & Autonomous Control)
D. Benders (TU Delft - Learning & Autonomous Control)
O. De Groot (TU Delft - Learning & Autonomous Control)
R.R. Negenborn (TU Delft - Transport Engineering and Logistics)
V. Reppa (TU Delft - Transport Engineering and Logistics)
L. Ferranti (TU Delft - Learning & Autonomous Control)
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Abstract
This paper presents a rule-compliant trajectory optimization method for the guidance and control of autonomous surface vessels. The method builds on Model Predictive Contouring Control and incorporates the International Regulations for Preventing Collisions at Sea - known as COLREGs - relevant for motion planning. We use these traffic rules to derive a trajectory optimization algorithm that guarantees safe navigation in mixed-traffic conditions, that is, in traffic environments with human operated vessels. The choice of an optimization-based approach enables the formalization of abstract verbal expressions, such as traffic rules, and their incorporation in the trajectory optimization algorithm along with the dynamics and other constraints that dictate the system's evolution over a sufficiently long receding horizon. The ability to plan considering different types of constraints over a long horizon in a unified manner leads to a proactive motion planner that mimics rule-compliant maneuvering behavior. The efficacy of the derived algorithm is validated in different simulation scenarios.
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