From Heights to the Deep Sea, a Review of Robots Interacting with Offshore Structures
Cyp Hooft Graafland, Jovana Jovanova
- 发表年份
- 2024
- 引用次数
- 5
- 访问权限
- 开放获取
摘要
An increasing energy demand forces companies to use the space available at sea, causing the number of offshore structures to increase. These offshore structures require maintenance. However, the harsh offshore environment makes this dangerous and costly for human workers. A solution would be the use of robots with manipulation capabilities. This literature review identifies robots that have manipulation capabilities and can be used to perform inspection, maintenance, and repair tasks on offshore structures. The environment of an offshore structure changes along its height. Therefore, the robots in this review are categorized based on the height they operate on. Starting at the top of wind turbines all the way down to the ocean floor. At great heights, unmanned aerial manipulators have some manipulation capabilities but are limited in their flight time and are vulnerable to disturbances. Climbing robots avoid the problem of strong winds at heights, but their manipulation capabilities are still limited. Legged robots are already used on the superstructure of offshore oil and gas platforms but would benefit from more autonomous operations. There is a limited number of robots operating in the splash zone. However, this number can be increased by making some adjustments to existing robots. Finally, various underwater robots with manipulation capabilities exist and are commercially available. However, they lack the ability to perform manipulation tasks autonomously. Overall, there are several robots that can or have the potential to perform manipulation tasks on offshore structures, but challenges need to be overcome before robots can be used on offshore structures on a large scale. Future research should focus on flexibility, durability, and autonomy. Overcoming these limitations will improve the safety, efficiency, and cost-effectiveness of offshore operations.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002