###### Abstract
[13] designed a wall climbing robot for automatic detection of weld defects in large storage tanks. The development of these underwater robots with cleaning, detection, and maintenance functions has also promoted the development of fluid-solid coupling theory, digital twin technology, and multi-information fusion technology [14, 15, 16, 17]. In summary, the above-mentioned ROVs focus on the design of the ROV itself without overall consideration of the design of the ROV's entire hardware and software system; the ROV designed can only complete single detection work, and it does not have the ability to complete work underwater and on water at the same time. To this end, this paper designs a complete set of ROV systems. Firstly, based on the idea of modularization, a new ROV is designed. The new ROV integrates the functions of traditional ROVs and the wall climbing robot. It not only has the ability of underwater detection of the above underwater observation robot but also the ability to climb the wall on the water for detection. Therefore, the new ROV has more application scenarios. The new ROV is mainly composed of the ROV buoyancy body in the upper part and the electromagnetic adsorption chassis in the lower part. The electromagnetic adsorption chassis can be disassembled, and the upper part of the ROV buoyancy body can be operated independently. The lower part of the electromagnetic adsorption chassis can walk on the ground and climb the metal wall. The installation holes are reserved on the electromagnetic adsorption site, and other equipment, such as manipulators, can be installed according to the work requirements to complete the expansion of ROV functions. Secondly, the structure design of a portable ground control box for real-time control of the ROV is completed. The control box integrates the operation,monitoring, and communication functions of ROVs and adopts industrial-grade hardware and redundant design. In addition, a large-capacity rechargeable lithium battery is installed inside of the control box, which can supply power to the entire ROV system and meet the use requirements of the entire system without a power supply. Finally, a set of control systems is designed independently, including upper computer control software and a lower computer control program. The control system can realize all of the functional requirements of the ROV and realize the integrated design of a high-efficiency, real-time, interactive, and reliable control system. The underwater motion ability of the detection ROV is key to the design. Therefore, it is necessary to study the thrust allocation and use corresponding methods to optimize it so as to ensure the rationality of its thrust allocation and the stability of its motion control. At present, common thrust allocation methods include the direct logic method, the pseudo-inverse method, the sequential quadratic programming method, the intelligent optimization algorithm, and so on. The advantages of the direct logic method and the pseudo-inverse method are simple in principle, and they are fast in finding solutions, but the two methods cannot solve the problem of over-saturation of thrust output when applied to some special thruster layouts. The advantage of the sequential quadratic programming method is that the operation speed is fast, which can improve the control efficiency of the propeller. Intelligent algorithms can now be used for thrust distribution, including neural networks, particle swarm optimization, genetic algorithms, etc. The algorithm principle is more complex, and the calculation amount is large [18; 19; 20]. [PERSON] et al. [21] proposed a thrust allocation method combining six degrees of freedom control normalization and the pseudo-inverse method. The simulation results show that this method can effectively solve the thruster saturation problem caused by the direct pseudo-inverse method, and it can be directly applied to solve the engineering problem of vector propulsion underwater vehicle motion control.