Regulations Aware Motion Planning for Autonomous Surface Vessels in Urban Canals
This work addresses collision avoidance and social compliance for autonomous vessels in unstructured urban canals, representing an incremental improvement in domain-specific motion planning.
The paper tackles motion planning for autonomous surface vessels in urban canals by proposing a regulations-aware framework based on local model predictive contouring control, showing more effective compliance with collision avoidance regulations compared to baseline methods in outdoor experiments.
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-compliance avoidance of moving obstacles with our motion planner. Additionally, we present experimental results in an outdoor environment