Print Email Facebook Twitter COLREGs-aware Trajectory Optimization for Autonomous Surface Vessels Title COLREGs-aware Trajectory Optimization for Autonomous Surface Vessels Author Tsolakis, A. (TU Delft Learning & Autonomous Control) Benders, D. (TU Delft Learning & Autonomous Control) de Groot, O.M. (TU Delft Learning & Autonomous Control) Negenborn, R.R. (TU Delft Transport Engineering and Logistics) Reppa, V. (TU Delft Transport Engineering and Logistics) Ferranti, L. (TU Delft Learning & Autonomous Control) Date 2022 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. Subject Autonomous Surface VesselsModel Predictive ControlTraffic Regulations To reference this document use: http://resolver.tudelft.nl/uuid:dbade853-678e-420c-9e8c-5f417587d6a9 DOI https://doi.org/10.1016/j.ifacol.2022.10.441 ISSN 1474-6670 Source IFAC-PapersOnLine, 55 (31), 269-274 Event 14th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles, CAMS 2022, 2022-09-14 → 2022-09-16, Kongens Lyngby, Germany Part of collection Institutional Repository Document type journal article Rights © 2022 A. Tsolakis, D. Benders, O.M. de Groot, R.R. Negenborn, V. Reppa, L. Ferranti Files PDF 1_s2.0_S2405896322024879_main.pdf 728.68 KB Close viewer /islandora/object/uuid:dbade853-678e-420c-9e8c-5f417587d6a9/datastream/OBJ/view