TRiLOGy - Sustainable Transportation and Logistics Over Water: Electrification, Automation, and Optimization
Image courtesy of MIT/AMS.
TRiLOGy will unlock the potential of transportation and logistics in urban waterways with electric and autonomous vessels by enabling safer, more sustainable and efficient operations. The project is divided into two main modules:
- 1. Autonomy
- 2. Fleet management
The autonomy module, which is the focus of our group, aims at developing autonomy tools for navigation in inland waterways, among other manned and unmanned vessels. The main challenges to ensure safe and efficient navigation of autonomous vessels in urban waters is that of generating safe trajectories that (i) take into account the goals expressed by the high-level integrated strategy, (ii) take into account the complex dynamics of the vessel and (iii) coordinate with other traffic participants.
Prof. Javier Alonso-Mora
Key collaborators: Prof. Bilge Atasoy and project partners
NWO Top Sector Water & Maritime: the Blue route, "Sustainable Transportation and Logistics over Water: Electrification, Automation and Optimization (TRiLOGy)", 2020-2024.
C1 J. de Vries, E. Trevisan, J. van der Toorn, T. Das, B. Brito, J. Alonso-Mora, Regulations Aware Motion Planning for Autonomous Surface Vessels in Urban Canals, in Proc. IEEE Int. Conf. on Robotics and Automation (ICRA), May 2022.
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-compliance avoidance of moving obstacles with our motion planner. Additionally, we present experimental results in an outdoor environment.