| Autor: |
Alvaro P. F. Negreiros, Wanderson S. Correa, André P. D. de Araujo, Davi H. Santos, João M. Vilas-Boas, Daniel H. N. Dias, Esteban W. G. Clua, Luiz M. G. Gonçalves |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Robotics and AI, Vol 9 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2296-9144 |
| DOI: |
10.3389/frobt.2022.788212 |
| Popis: |
Strategic management and production of internal energy in autonomous robots is becoming a research topic with growing importance, especially for platforms that target long-endurance missions, with long-range and duration. It is fundamental for autonomous vehicles to have energy self-generation capability to improve energy autonomy, especially in situations where refueling is not viable, such as an autonomous sailboat in ocean traversing. Hence, the development of energy estimation and management solutions is an important research topic to better optimize the use of available energy supply and generation potential. In this work, we revisit the challenges behind the project design and construction for two fully autonomous sailboats and propose a methodology based on the Restricted Boltzmann Machine (RBM) in order to find the best way to manage the supplementary energy generated by solar panels. To verify the approach, we introduce a case study with our two developed sailboats that have planned payload with electric and electronics, and one of them is equipped with an electrical engine that may eventually help with the sailboat propulsion. Our current results show that it is possible to augment the system confidence level for the potential energy that can be harvested from the environment and the remaining energy stored, optimizing the energy usage of autonomous vehicles and improving their energy robustness. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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