Unmanned Surface
Unmanned surface vehicles (USVs) are autonomous robots operating on water, primarily aimed at improving efficiency and safety in various maritime tasks. Current research heavily focuses on enhancing USV autonomy through advanced control algorithms (like model predictive control and adaptive control), robust state estimation techniques incorporating sensor fusion (e.g., camera, radar, sonar), and improved navigation in challenging conditions (e.g., strong waves, GPS denial). This work is significant for advancing maritime operations, enabling applications such as environmental monitoring, search and rescue, and collaborative tasks with other unmanned systems (e.g., UAVs), ultimately leading to safer and more efficient maritime activities.
Papers
Dynamic Obstacle Avoidance of Unmanned Surface Vehicles in Maritime Environments Using Gaussian Processes Based Motion Planning
Jiawei Meng, Yuanchang Liu, Danail Stoyanov
Benchmarking Vision-Based Object Tracking for USVs in Complex Maritime Environments
Muhayy Ud Din, Ahsan B. Bakht, Waseem Akram, Yihao Dong, Lakmal Seneviratne, Irfan Hussain
Model predictive control-based trajectory generation for agile landing of unmanned aerial vehicle on a moving boat
Ondřej Procházka, Filip Novák, Tomáš Báča, Parakh M. Gupta, Robert Pěnička, Martin Saska
Towards Design and Development of a Low-Cost Unmanned Surface Vehicle for Aquaculture Water Quality Monitoring in Shallow Water Environments
Aiyelari Temilolorun, Yogang Singh
Multiple Ships Cooperative Navigation and Collision Avoidance using Multi-agent Reinforcement Learning with Communication
Y. Wang, Y. Zhao