| Autor: |
Yijie Chu, Qizhong Gao, Yong Yue, Eng Gee Lim, Paolo Paoletti, Jieming Ma, Xiaohui Zhu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Drones, Vol 8, Iss 10, p 540 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2504-446X |
| DOI: |
10.3390/drones8100540 |
| Popis: |
Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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