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Traditional underwater robots have many shortcomings in terms of resistance to sea currents, stability and functionality. In order to improve the efficiency and quality of underwater operations, this paper proposes and designs a new underwater robot, the navigation and crawl underwater unmanned vehicle (NCUUV), it has two motion modes: swimming and crawling. In order to enable the robot to have the ability to switch motion modes, this paper designed a motion mode switching mechanism, and verified the effectiveness of the mechanism through experiments, which proved that the mechanism has good motion reliability and accuracy. In order to control NCUUV to smoothly switch the motion mode, a controller based on the central pattern generator (CPG) was developed. The upper controller reconstructs the CPG network in the middle controller according to the feedback information of the acoustic rangefinder. The CPG network in the middle controller has two configurations: a triangular fully symmetrical network and a hexagonal fully symmetrical network, and the CPG network can be freely changed between the two configurations according to the instructions of the upper controller. These two configurations control NCUUV’s swimming and crawling respectively, so as to realize the smooth switching between swimming and crawling. The experimental result shows that this control mechanism of motion mode switching can enable NCUUV to stably realize motion mode switching and the switching process is smooth and reliable.

To meet the challenges of different underwater environments, improve the operating efficiency of the underwater robots, this paper designed the spherical underwater robot with a hybrid propulsion devices (water-jet-device and propeller-device). The robot we designed has different motion modes such as propeller-drive, water-jet-drive, and hybrid drives. It can not only realize speed switching in complex environments, but also enhance motion stability and improve operation efficiency. Then, to analyze the motion characteristics of the SUR, this paper assembled the hybrid propulsion spherical underwater robot (HPSUR). Finally, this paper carried out the motion experiments in the pool, including forward-motion experiments and rotation-motion experiments. The motion experimental result showed that the improved hybrid propulsion devices we designed had better performance, improved the motion speed and work efficiency.

It is believed that the extraordinary propulsion performance of aquatic animals originates from wave-like body movements. To be specific, they rely on body and/or tail fin (BCF) propulsion to allow swimming to perform more effective movement at higher speeds and accelerations. From the perspective of bionics, a growing number of scientists have proposed soft prototype robot. This study introduces the design, manufacture and characterization of a magnetically controlled soft tadpole-like robot, which is propelled by BCF. The robot with a body length of 20 mm exhibits excellent motion performance, with the speed of 12.6 mm/s under 12 Hz time-varying magnetic field. This article also discusses the propulsion mechanism of the tadpole-like robot, which provides clues for the design of the bionic underwater robot for latecomers.

Several animal species self-organize into large groups to leverage vital behaviors such as foraging, construction, or predator evasion. With the advancement of robotics and automation, engineered multi-agent systems have been inspired to achieve similarly high degrees of scalable, robust, and adaptable autonomy through decentralized and dynamic coordination. So far however, they have been most successfully demonstrated above ground or with partial assistance from central controllers and external tracking. Here we demonstrate an underwater robot collective that realizes full spatiotemporal coordination. Using the example of fish-inspired evasive maneuvers, our robots display alignment, formation control, and coordinated escape, enabled by real-time on-board multi-robot tracking and local decision making. Accompanied by a custom simulator, this robotic platform advances the physically- validated development of algorithms for collective behaviors and future applications including collective exploration, tracking and capture, or environmental sampling.

We present a Computational Fluid Dynamics (CFD) simulation of a Negative Pressure Effect Plate (NPEP) that generates a large force for stabilizing the positions and orientations of underwater robots. For designing NPEPs and improving the mathematical model of NPEPs, we applied a CFD method to understand hydrodynamic phenomena occurring around the NPEP. For the simulation, we analyze the pressure and flow distributions inside of the NPEPs with different diameters. We also conducted an experiment to evaluate the performance of one NPEP and for comparison with CFD results. Comparison of the experimental and numerical results, revealed some clues for design and prediction model improvement of the NPEP.

This manuscript describes a pressure sensor equipment for underwater robot external attachment. It is difficult to add sensors to many underwater robots. Most pressure sensors have a diaphragm plate, and the pressure sensor must be exposed to the environment to deform the diaphragm plate. Therefore, to add a pressure sensor to an underwater robot, it is generally necessary to redesign both the outer shell and the robot’s inner structure. To solve this problem, we propose encapsulating a pressure sensor in a plastic film bag. Vacuum packaging technology is applied to fabricate the sensor equipment. This technique is called the robot packaging method, and it is possible to fabricate the sensor equipment rapidly and inexpensively. This manuscript shows experimental results that it is necessary to encapsulate a sufficient amount of insulating fluid in the plastic film bag to fabricate the pressure sensor equipment by the robot packaging method.

In future ocean development, it is considered that many tasks will be achieved by cooperative motions of several underwater robots. However, no research has been studied on the cooperative work of underwater robots. We have proposed a cooperative control method for space robots. In this paper, as the first step of development of cooperative control methods for underwater robots, our proposed resolved acceleration control method for underwater vehicle-manipulator system is applied to cooperative manipulations of a floating object by underwater robots. To validate the control method, computer simulations are done. The simulation results show the effectiveness of the control method.

The development of a country is inseparable from resources. With the shortage of land resources, all countries begin to explore underwater resources. Whether now or in the future, underwater robots are crucial equipment for all countries in the exploration and exploitation of Marine resources, and are a hot research topic in today's era. This paper introduces and studies the underwater manipulator studied by several foreign companies in recent years by looking up relevant literature and data, and at the same time briefly introduces the underwater manipulator studied by more mature research institutes and universities in China in recent years. On this basis, several common single control methods and complex control methods as well as relevant application examples are briefly introduced and analyzed. Finally, the future development and research direction of this hot topic are prospected.

This article introduces the development of a controller unit to control a multispectral imaging system applied in an underwater robot for collecting geoscientific data from flooded mines. The paper describes other geoscientific sensors of the robot-platform and explains the theory of the multispectral unit. During the development it was a great challenge to satisfy the size restrictions of the circuit and the delay of the electronics. It is also described that how is this unit works within the robot’s system and introduces what we achieved with it during the last 2 years of laboratory and real-environmental testing.

Underwater robots provide great possibilities for people to detect the marine environment. Robots need to keep moving stability, need to ensure the safety of the robot during the movement. A novel spherical underwater robot (SUR V) with hybrid propulsion devices that divided into two parts- vectored water-jet and propeller thrusters. A camera is added at robot to monitor the environments. To analyze the motion characteristics of the SUR V, the computational simulation is calculated in ADAMS and ANSYS CFX respectively. The simulation results verify the performance of the improved spherical underwater robot. Finally, the thrust experiments were conducted that evaluate the performance of the hybrid thruster. The thrust experiment proves that in the improved hybrid thruster proposed in this paper, the maximum thrust of the propeller thruster has increased by 4 times than before.

This paper presents an innovative modular autonomous underwater vehicle (MARA) developed for the exploration of underwater confined spaces such as underwater caves, flooded underground mines or complex tight infrastructures in underwater environments. The particular mission scenario of exploration of flooded underground mines was used as a key driver for the robot development. The autonomous underwater vehicle is described from the mechanical, hardware and software points of view. The availability of the INESC TEC underwater systems test tank and access conditions to Porto harbour and the Urgeirica mine allows for easy robot field validation. Preliminary results are also presented and discussed.

Monitoring missions in confined underwater environments such as nuclear storage ponds or industry tanks call for highly maneuverable fully autonomous micro underwater robots. In this work, we target this challenging scenario with the new low-cost open-source HippoCampusX platform. We present a modular software and hardware architecture which is easily adaptable to mission specific requirements. Our system is part of the PX4-environment [1] and constitutes PX4’s first underwater extension including a SITL simulation. We conduct a series of experiments to demonstrate HippoCampus’ agile maneuvering capabilities and validate the derived dynamic model.

This paper presents an Autonomous Underwater Vehicle (AUV) with a dynamic configuration of its actuation. The AUV is able to modify its configuration online (at each sampling time) during its missions. A procedure to optimize the dynamic configuration with respect to energy-like criterion is introduced. The simulation results are shown to prove the efficiency of a dynamic management of the actuation configuration.

In this paper the usage of Transfer Learning method for object detection in underwater environment is experienced and evaluated. Deep learning method of YOLO is utilized for detection of different types of fish underwater. A ROV equipped with camera is employed for video streaming underwater and the data has been analyzed on the main computer Our experimental results confirmed improvement in the mAP by 4% using transfer learning.

the article discusses the features of the synthesis of images of artificial objects with the aim of their search and recognition in the vision system of an underwater robot. The results of research and development to given: a database - a classifier of features that allows you to store information about the reference underwater objects; software module for generating images of reference objects and their insertion in a sonar image file. In the modeling program for the synthesis of underwater objects in the HBO image, the algorithms for introducing objects used by taking into account the peculiarities of the formation of HBO images by sonar. The program allows implementing several objects of spherical, cylindrical and cubic shapes with specified parameters, which allows simulating the situation of search for an artificial object according to given geometric features against the background of other objects. The developed software allows simulating underwater objects according to the characteristics close to real objects with the help of their preliminary processing and subsequent implementation in real HBO images

In recent years, many countries have gradually turned their development judgments to marine development, put forward the goal of building a powerful marine development country, underwater robots have become the hotspot of current development. The propulsion mechanism of underwater vehicle is the key technology that restricts the development of robot. In order to meet the needs of high efficiency propulsion of underwater vehicle, the model of UPR-UPU-UR vector propulsion mechanism is designed. According to the principle of parallel mechanism, Calculating the degree of freedom of the mechanism. Then the inverse solution of position is derived from the position relation. The position workspace simulation of the mechanism is carried out, and the simulation results are compared with the theoretical analysis results, which proves the correctness of the design and theoretical derivation. The parallel mechanism can achieve multiple directions attitude rotations, which provides a reliable theoretical basis for underwater vehicle.

To make the movement of the spherical underwater robot more stable and easier to control, it is necessary to design a controller that can hover autonomously. According to the dynamic equation, we solved the transfer function of the spherical underwater robot in the dive process. Next, we designed the fuzzy PD controller which was easy to control, nonlinear and automatically adjustable. We used Simulink to build the hover motion simulation model for the spherical underwater robot, including using fuzzy PD controller and without fuzzy PD controller, and we carried out the comparative experiments of two simulation models. Then we applied the fuzzy PD controller to the hover motion of the spherical underwater robot, and carried out hover motion experiments. The experimental results showed that the fuzzy PD controller had better performance, and improved the stability of hover motion of the spherical underwater robot.

In order to meet the requirements of fast detection and classification of underwater targets during intelligent underwater robot operation, an improved YOLOv3 algorithm named YOLOv3-UW algorithm is proposed to improve the detection accuracy and detection speed. Compared with the YOLOv3 algorithm, the YOLOv3-UW algorithm improves the clusters algorithm of data sets, optimizes the network structure, and improves the residual module. The final experimental results show that detection speed and detection accuracy of the YOLOv3-UW algorithm are higher than the YOLOv3 algorithm.

The paper is dedicated to solving of on-line fault detection and identification for thrusters of underwater robots. To detect and estimate the possible typical faults, bank of sliding mode observers is proposed. The new approach to construct such a bank of observers, based on the reduced model of the initial systems, is suggested and developed. This approach allows reducing complexity of the observers. The effectiveness of the proposed system was confirmed by computer simulation.

Navigation systems in underwater robots refer to the process of avoiding obstacles. The navigation system has uncertainty values at the input and output. In this paper, the method of an automatic navigation system uses fuzzy logic. Fuzzy logic can control and predict from a dynamic system. Fuzzy logic is Mamdani fuzzy logic. Mamdani's fuzzy logic was embedded in the underwater robot navigation system. The embedded system is to build robotic behavior. The input in the navigation system is the distance value of the sonar sensor. The output in the navigation system is the value of the motor velocity. The results of the navigation system with the Mamdani fuzzy logic method have a good performance.

Marine image recognition is a basic research of underwater robots. Because the marine images are weak, variable lighting, low contrast and blurring, marine image recognition is a difficult task. In the traditional marine image recognition methods, feature extraction depends on manual guidance and prior knowledge. And as the amount of data increases, the efficiency is drastically reduced. So, a marine biological identification method based on deep convolutional neural network is proposed. The marine biological image recognition based on deep convolutional neural network (MB-DCNN) has few structural parameters, the accuracy rate reaches 85.9%.

Optical detection using underwater camera is an important means for underwater robot to detect submarine cables. But underwater optical images are often affected by underwater scattering and absorption characteristics, resulting in poor imaging quality and more noise interference. The images collected by the underwater robot need to be processed accordingly, and the external interference objects are automatically eliminated in order to observe the location and specific state of the submarine cable body more clearly. In this paper, an image recognition method for optical detection of underwater robot for submarine cables will be presented.

Emergency ship hull repair is a vital damage control procedure that makes the difference between reaching\ud the next port and losing a ship. For repairs to be made, ship hull breaches must be quickly located and patched. In this paper, we propose a searching algorithm to be used by a\ud homogeneous swarm of autonomous underwater robots to\ud inspect a ship hull and identify breaches. Inspired by methods tested in 2D environments, we combine aspects of previous studies and implement them in a 3D environment. We compare two approaches designed to achieve complete area coverage of a large section of ship hull and identify the approach that yields the shortest discovery time and highest accuracy. Our system is verified within the Webots software simulated environment and shows that the system is resilient to sensor noise and failure of a fraction of the robot population.

Bionic robotic fish is an important branch of underwater robot research. At present, most of the bionic robotic fish research focuses on the behavior of a single robot but ignores the influence of the robot swarms. Robot swarms play an important role in cases focusing on the environment. It is necessary to develop robot cruising formation for water environment detection. In this paper, we use Computational Fluid Dynamics (CFD) method to simulate three kinds of diamond bionic robotic fish cruising formations in the typical hydrological environment. The efficiency of three cruising formations is compared by changing the composition of diamond formations and the spacing between bionic robotic fishes. The results show that the greater thrust and the smaller lateral power loss lead to the higher efficiency of the bionic robotic fish formation. The average thrust of bionic robotic fish formation is large when the spacing between the front and rear fishes is small. When the spacing between abreast bionic robotic fishes is large, the average lateral power loss caused by the swing of fishes is small. According to the results, the suitable formation can be selected for an efficient cruise under different environments, tasks and real-time communication requirements.

Amphibious robots are the combination version of underwater and land robots. It is more versatile. Compared with simple land robot and underwater robot, it could adapt to more complex external environment, do some detective works, such as detect soil quality, detect water quality, and it could also be used for coastline patrol in military. It has a very broad development prospect. Compared with quadruped or hexapod robots, amphibious biped robots have simpler structure and easier maintenance. In this paper, a duck-like robot was developed. Firstly, this paper introduced the mechanical structure of swimming-fin of duck-like robot; secondly, introduced the hardware and software platform of the duck-like robot; thirdly, modeled and analyzed leg of this duck-like robot. Then, basic characteristics evaluation of a duck-like Robot has been carried out.

This research aims to improve the collaboration ability and stability of the Spherical Underwater Robots (SUR III). According to our previous researches in last few years, the SURIII has no control stability module. This paper designed a new torque gyro control and PID control devoted to improve the stability of SUR III. In this new system, we used a gyro sensor and PID control to design a closed-loop control module to perform terrestrial underwater efficiently. Regarding the spherical robot mechanical structure and dynamic model, the robot control module is designed, and set up to complete underwater experiments. In the underwater experiment, the SUR III can stability motion. A certain offset occurs of SUR III under the disturbance of the wind. After the adjustment of the balance control module, the SUR III balance is quickly restored. In addition, it is certainly worth analyzing the underwater motion to evaluate the performance of the robot stability motion.

This paper studies the influence of various parameters on the performance of the underwater snake-like robot's thrust, including swimming gait, motion parameter, and tail shape. An underwater snake-like robot prototype with a caudal fin is introduced. Three types of gaits are performed on the prototype with two different shapes of the tail, respectively. By changing the motion parameters of the three swimming gaits, a total of one hundred and fifty series of experiments are implemented. The measurement results enable us to find out the relationship between these various parameters and the thrust generated by the underwater snake-like robot.

A sea cucumbers detection method based on SSD and depthwise separable convolution is proposed. Firstly, sea cucumbers images taken by underwater robot are enhanced by Multi Scale Retinex, which can make underwater images clearer. MobileNet-SSD which uses a 13-layer depthwise separable convolution as basic feature extractor is trained to detect the sea cucumbers and model quantification is applied to the model to further reduce the model size and improve detection speed. Experimental results demonstrate that the mean average precision of improved SSD reaches 89.41 %, the detection precision for underwater sea cucumbers is 93.76% and the recall ratio is 91.17%, the detection speed can reach 19.8f/s in CPU mode which is no longer limited by the performance of computer. Compared with other methods for object detection, the improved SSD can reach a high level of both detection precision and speed, which can realize the rapid and accurate detection of sea cucumbers.