Design and optimization of AI enabled underwater robotsWith the advancement of technology, underwater robots have been used in a variety of application such as underwater welding, offshore oil and gas development, underwater search and rescue, the survey of underwater materials, marine research and so on 1. Such task is carried out in a harsh underwater environment 2 and with the aid of high-tech underwater equipment such as sensors and cameras which are used for inspection, diving regulators to regulate the robot’s buoyancy and propellers for its manoeuvrability 5. Underwater robots are usually connected by a cable, which is connected to its control centre, where the operator controls the robot. This, however, limits the robot’s full capability due to the length of the cable and the operator’s human error 5. Thus, artificial-intelligence enabled underwater robots are gaining popularity as they are not connected by any cables nor do they need to be manned 5. But, due to the complexity of the underwater environment, the task carried out is usually very difficult 3.
Studies conducted thus far, have shown that the robot’s rapidity and manoeuvrability also determine whether a robot can perform its task accurately 2. To be more specific, an underwater robots’ capability to perform its task can be narrowed down to the frame design and the propellers capability to transport itself 2.Studies conducted have shown that a small size, lightweight, flexible, portable and cost-effective robot have been the focus of underwater research 2, 4. However, bulky and heavy underwater robots have been proven to reach a depth that lightweight robots could only hope to achieve. Furthermore, lightweight underwater robots have a lot of control instability and a small load capacity which is due to their decentralized independent underwater propellers. Bulky and heavy underwater robots, on the other hand, has a powerful centralized underwater propeller which often has a complicated control algorithm. But due to its size, bulky and heavy underwater robot lacks rapidity and manoeuvrability 1. Past research has shown that changing the frame and propellers may optimize the robot’s capability, but little research is done in ensuring that the underwater robot can both achieve manoeuvrability, rapidity and reach deeper depths while maintaining stable control.
Therefore, the objective of this study is to design and optimize an underwater robot that has manoeuvrability, rapidity as well as the capability to reach deeper depths while maintaining a stable control. By designing the frame of the robot to one that has a parabolic, semi-circular, semi-ellipse, Nystrom or a Myring curve, the robot will have a better hydrodynamic characteristic and a more streamlined rotary body, this will help reduce the resistance experienced by the robot thus increasing rapidity and manoeuvrability. Also, by implementing a yaw, pitch, roll propeller which has six degrees of freedom in addition to its diving regulators, the robot can be able to reach deeper depths. Furthermore, simulations will be carried out to determine the shape that gives the robot more rapidity and manoeuvrability. Hence with the result attained the underwater robot will have a better capability in performing it’s given task.Reference1 J.
S. Aibin Zhu, Ying Li, Mengke Wu, Xiaodong Zhang, “Small Cluster Underwater Robot design with Variable Pitch Propeller,” in 2018 15th International Conference on Ubiquitous Robot (UR), 2018, p. 235.2 K.-W. M. Qian Chen, Bo Huang, Ming Zhing, “Design and Optimization of Mini Underwater Robot Based on ANSYS and CAESES,” in 2018 2nd International Conference on Robotics and Automation Sciences, 2018, p.
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Feng, “Design of an ocean current roaming underwater robot,” in 2017 4th International Conference on Systems and Informatics (ICSAI), 2017, pp. 229-233.4 J. H. R. Sanjib Kumar Deb, Tuton Chandra Mallick, Ms.
Juliana Shetara, “Design and construction of an underwater robot,” in 2017 4th International Conference on Advances Electrical Engineering (ICAEE), 2017, p. 281.5 M. Käßler, Thomas Rauschenbach, “Underwater robots on course to deep sea,” 2010, Online, Available: https://www.fraunhofer.de/en/press/research-news/2010/11/underwater-robots-on-course-to-the-deep-sea.
html . Accessed: 11- Sep- 2018.