Regulations Aware Motion Planning for Autonomous Surface Vessels in Urban Canals
J.M. de Vries (Student TU Delft)
E. Trevisan (TU Delft - Learning & Autonomous Control)
J. van der Toorn (Student TU Delft)
T. Das (Student TU Delft)
B.F. Ferreira de Brito (TU Delft - Learning & Autonomous Control)
J. Alonso-Mora (TU Delft - Learning & Autonomous Control)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs) that accounts for dynamic and static obstacles. Our method builds upon local model predictive contouring control (LMPCC) to generate motion plans satisfying kino-dynamic and collision constraints in real-time while including regulation awareness. To incorporate regulations in the planning stage, we propose a cost function encouraging compliance with rules describing interactions with other vessels similar to COLlision avoidance REGulations at sea (COLREGs). These regulations are essential to make an ASV behave in a predictable and socially compliant manner with regard to other vessels. We compare the framework against baseline methods and show more effective regulation-compliant avoidance of moving obstacles with our motion planner. Additionally, we present experimental results in an outdoor environment.