aColor: Mechatronics, Machine Learning, and Communications in an Unmanned Surface Vehicle
Abstract
The aim of this work is to offer an overview of the research questions, solutions, and challenges faced by the project aColor ("Autonomous and Collaborative Offshore Robotics"). This initiative incorporates three different research areas, namely, mechatronics, machine learning, and communications. It is implemented in an autonomous offshore multicomponent robotic system having an Unmanned Surface Vehicle (USV) as its main subsystem. Our results across the three areas of work are systematically outlined in this paper by demonstrating the advantages and capabilities of the proposed system for different Guidance, Navigation, and Control missions, as well as for the high-speed and long-range bidirectional connectivity purposes across all autonomous subsystems. Challenges for the future are also identified by this study, thus offering an outline for the next steps of the aColor project.
Cite
@article{arxiv.2003.00745,
title = {aColor: Mechatronics, Machine Learning, and Communications in an Unmanned Surface Vehicle},
author = {Jose Villa and Jussi Taipalmaa and Mikhail Gerasimenko and Alexander Pyattaev and Mikko Ukonaho and Honglei Zhang and Jenni Raitoharju and Nikolaos Passalis and Antti Perttula and Jussi Aaltonen and Sergey Andreev and Markus Aho and Sauli Virta and Moncef Gabbouj and Mikko Valkama and Kari T. Koskinen},
journal= {arXiv preprint arXiv:2003.00745},
year = {2020}
}
Comments
Paper was originally submitted to and presented in the 8th Transport Research Arena TRA 2020, April 27-30, 2020, Helsinki, Finland