Kalman Filter and PID Application on Underwater Vehicles

There have been increased developments in ocean exploration using autonomous underwater vehicles (AUVs) and unmanned underwater vehicles (UUVs). However, the contrast of underwater images is still a major issue for application. It is difficult to acquire clear underwater images around underwater vehicles. Since the 1960s, sonar sensors have been extensively used to detect and recognize objects in oceans. Due to the principles of acoustic imaging, sonar-imaged images have many shortcomings, such as a low signal to noise ratio and a low resolution. Consequently, vision sensors must be used for short-range identification because sonars yield to low-quality images. This thesis will concentrate solely on the optical imaging sensors for ocean observing. Although the underwater optical imaging technology makes a great progress, the recognition of underwater objects also remains a major issue in recent days. Different from the common images, underwater images suffer from poor visibility due to the medium scattering and light distortion. First of all, capturing images underwater are difficult, mostly due to attenuation caused by light. The random attenuation of the light mainly causes the haze appearance along with the part of the light scattered back from the water. In particular, the objects at a distance of more than 10 m are almost indistinguishable because of absorption. Furthermore, when the artificial light is employed, it can cause a distinctive footprint on the seafloor. In this paper, we will analysis the recent trends of ocean exploration approaches.

In this chapter, the receding horizon Kalman filter is applied to underwater navigation systems. The ocean covers about two-thirds of the earth and has a great effect on human beings. However, the ocean is overlooked while we focus our attention on land and atmospheric issues; we have not been able to explore the full depths of the ocean, its abundant livings and non-living resources. For example, only recently we have discovered, by using manned submersibles, that a large amount of methane and carbon dioxide comes from the seafloor and extraordinary groups of organisms live in hydrothermal vent areas. However, a number of complex issues due to the unstructured and hazardous undersea environment make it difficult to survey in the ocean even though today’s technologies have allowed humans to land on the moon and robots to travel to Mars. Unmanned underwater vehicles (UUVs) can help us better understand marine and other environmental issues, protect the ocean resources of the earth from pollution, and efficiently utilize them for human welfare. The UUV is a platform for a variety of sensors: acoustic, magnetic, gravimetric and chemical ones. Most commercial UUVs are tethered and remotely operated, referred to as remotely operated vehicles (ROVs). Extensive use of manned submersibles and ROVs are currently limited to a few applications because of very high operational costs, operator fatigue and safety issues. The demand for advanced underwater vehicle technologies is growing and will eventually lead to fully autonomous and reliable underwater vehicles. Autonomous underwater vehicles (AUVs) were initially developed to perform missions that were not easy for ROVs and manned underwater vehicles. Since the autonomy allows AUVs to be used for risky missions such as a mine countermeasure (MCM) or under-ice operations, AUVs are replacing ROVs towed vehicles as well as manned underwater vehicles (Whitcomb, 2000). For detailed ocean surveys, an AUV acts as a more stable platform for precision sensors than ROVs or towed vehicles because an AUV is not subject to physical disturbances transmitted along the cable to the surface vessel. This absence of physical attachment also allows AUVs to measure ocean characteristics at specific depths and perform bottom-following missions as owing to its autonomy. In short, An AUV provides marine researchers with a new form of access to deeper ocean. For an AUV to successfully complete a typical survey mission, it must follow a path specified by the operator as closely as possible and arrive at a precise location for collecting data. When an AUV is not able to follow the path accurately during the mission, critical Source: Kalman Filter, Book edited by: Vedran Kordic, ISBN 978-953-307-094-0, pp. 390, May 2010, INTECH, Croatia, downloaded from SCIYO.COM

Unmanned Underwater Vehicle (UUV) is one of the systems that have a complex characteristic. UUV usually used to obtain data, mapping and underwater survey. One of a complexity that UUV have is based onuncertainty and non-linearity of hydrodynamics parameter. Besides that, UU V which studied in this paper have 6 degree of freedom, so it has also a lot parameter. And to handle that, a bigger system need to divide into some sub-system, the divided is based on control needed. To handle a movement of UUV, it’s important to build a control system that effective and efficient and a writer choose PID and Sliding-PID (SMC-PID) as a controller Modeling system used to linearize a non-linier system from UUV, linearizing around the equilibrium point. Then make a model into a state space, these state space uses for a controlling. For a control system building and respond system from an UUV movement, MATLAB program is needed Keywords: UUV, PID control, Sliding-PID, MATLAB Simulink, Linier System

Based on the application of important water area blockade, a new discontinuous guidance approach of an unmanned underwater vehicle (UUV) perpendicularly towards side of surface ship is proposed, and a hardware-in-the-loop simulation (HILS) system is established to demonstrate this guidance approach. This approach can be described as follows: a near-surface straight trajectory which is perpendicular to the predicted ship trajectory is figured out by detection device of UUV which is hidden underwater after the ship target is located. When the horizontal distance between UUV and the ship target meets start-up condition, UUV climbs to a certain depth near the sea surface and then runs along the horizontal straight trajectory. During its motion, UUV periodically measures the sight line between the UUV and ship target. In order to restrain the horizontal rotation of the sight line, a discontinuous guidance approach is proposed by using the deviation of the two adjacent sight lines and the distance between the UUV and the ship target to adjust the UUV’s velocity. After certain times of adjustment of the UUV’s velocity, UUV impacts the side of ship target perpendicularly with required accuracy. This near-surface discontinuous guidance approach makes it possible for UUV to be guided through optical or radar detection. Further discussions are made including miss distance caused by this proposed guidance approach, cycle of sight line detection, UUV’s non-attack zone and UUV start-up condition. Finally, a set of HILS is carried out to demonstrate the performance of the discontinuous guidance approach on an experimentally validated UUV model.

This paper demonstrates the design and development of a novel system which comprises of a command boat and Unmanned Underwater Vehicle (UUV) with which, one is able to extend the range of operation of the Remotely Operated underwater Vehicle (ROV) which is limited by the length of tether. The UUV proposed in our system can be utilized along with features and functionality of existing designs, along with an added advantage of incorporating additional accessories depending upon the application. The system comprises of three components: a control unit, command boat and an UUV. The control unit is situated in any physical planar surface. The operator controls the command boat–UUV system wirelessly, which are linked using a tether. The UUV can assist in exploration, research, search and recovery etc. In the case of search and recovery, the command boat is guided to the required location, then the system identifies the retrievable using camera and appropriate sensors, then the UUV is deployed which is further guided towards the retrievable, and a pair of robotic arms with tangible gripper recovers the retrievable (weighing atmost 2kg). The UUV and the retrievable is docked to the command boat and the system is acquired, hence completing the operation.

This manuscript considers a team of Unmanned Underwater Vehicles (UUVs) such that each UUV measures the arrival time of sound signal generated from the evader. The purpose of the UUV team is to intercept the underwater evader based on the arrival time measurements. We present both the motion control for the UUV team and the algorithm to estimate the evader position in real time. In this manuscript, the UUVs chase the evader while preserving a 3D spherical formation. Moreover, the formation size is controlled adaptively to assure the convergence of the evader estimation. Our tracking approach doesn't require global localization of every UUV. The proposed approach only requires that the central UUV measures the relative position of any other UUV using proximity sensors. Simulations are utilized to verify the effectiveness of the proposed method.

Morphing hull concept for underwater vehicles

In response to the problem of decreased collaborative control performance in underwater unmanned vehicles (UUVs) with communication packet loss, a GRU-KF method for multi-UUV control that integrates a gated recurrent unit (GRU) and a Kalman filter (KF) is proposed. First, a UUV feedback linearization model and a current model are established, and a multi-UUV controller-based leader–follower method is designed, using a neural network-based radial basis function (RBF) to counteract the uncertainty effects in the model. For scenarios involving packet loss in multi-UUV collaborative communication, the GRU network extracts historical temporal features to enhance the system’s adaptability to communication uncertainties, while the KF performs state estimation and error correction. The simulation results show that, compared to compensation by the GRU network, the proposed method significantly reduces the jitter level and convergence time of errors, enabling the formation to exhibit good robustness and accuracy in communication packet loss scenarios.

Unmanned Underwater Vehicles (UUVs) are popular tools nowadays in marine exploration and oceanographic research. How to navigate an UUV in unknown or unstructured environments without long baseline or short baseline information are always a challenging problem. Side Scan Sonar (SSS) are common payloads on UUVs for navigation and environment detection. This study proposes a real time SSS seafloor mapping method combining the motion information and the observation model of the sonar to localize the UUVs. The working principle of SSS, sonar footprint region calculation and the acoustic velocity in water are considered during the feature localization procedure. An occupancy grid mapping algorithm is then used to map the seafloor combining the uncertainties of UUV's motion and measurement errors from the real time observations. Scanlines' information instead of the SSS images during the landmarks' position detection process was implemented on an UUV and experimental results conducted in a sandy seabed with concrete targets are demonstrated.

Underwater operating platforms face difficulties regarding power supply and communications. To overcome these difficulties, this study proposes a hybrid surface and underwater vehicle (HSUV) and presents the development of the platform, control algorithms, and results of field tests. The HSUV is capable of supplying reliable power to the unmanned underwater vehicle (UUV) and obtaining data in real time by using a tether cable between the UUV and the unmanned surface vehicle (USV). The HSUV uses global positioning system (GPS) and ultra-short base line sensors to determine the relative location of the UUV. Way point (WP) and dynamic positioning (DP) algorithms were developed to enable the HSUV to perform unmanned exploration. After reaching the target point using the WP algorithm, the DP algorithm enables USV to maintain position while withstanding environmental disturbances. To ensure the navigation performance at sea, performance tests of GPS, attitude/heading reference system, and side scan sonar were conducted. Based on these results, manual operation, WP, and DP tests were conducted at sea. WP and DP test results and side scan sonar images during the sea trials are presented.

In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color distortion and target feature blurring, which greatly affect the detection accuracy of underwater object detection. Although deep learning-based algorithms have achieved state-of-the-art results in the field of object detection, most of them cannot be applied to practice because of the limited computing capacity of a low-power processor embedded in unmanned underwater vehicles. This paper proposes a lightweight underwater object detection network based on the YOLOX model called LUO-YOLOX. A novel weighted ghost-CSPDarknet and simplified PANet were used in LUO-YOLOX to reduce the parameters of the whole model. Moreover, aiming to solve the problems of color distortion and unclear features of targets in underwater images, this paper proposes an efficient self-supervised pre-training joint framework based on underwater auto-encoder transformation (UAET). After the end-to-end pre-training process with the self-supervised pre-training joint framework, the backbone of the object detection network can extract more essential and robust features from degradation images when retrained on underwater datasets. Numerous experiments on the URPC2021 and detecting underwater objects (DUO) datasets verify the performance of our proposed method. Our work can assist unmanned underwater vehicles to perform underwater object detection tasks more accurately.

In order to solve the problem that the traditional navigation algorithm is unavailable for Unmanned Underwater Vehicles (UUVs) navigation in the polar region, a transversal navigation algorithm for polar UUV navigation is proposed in this paper. Traditional latitude and longitude is redefined in the transversal navigation algorithm to overcome the problems caused by the rapid convergence of the meridians in high latitude areas. Based on the transversal latitude and longitude coordinate system, the relevant frames are also redefined. According to the frames, the error equations of polar UUV navigation are established. Then, the states and observation equations are proposed. Considering the characters of UUV, OCTANS and Doppler velocity log (DVL) are chosen to assist the polar UUV navigation. Transversal Strapdown Inertial Navigation System (SINS), OCTANS and DVL form the integrated navigation algorithm. An adaptive Kalman filter (AKF) is introduced to realize the data fusion. Compared with the traditional SINS, the performance of the transversal navigation algorithm proposed in this paper is verified. The simulation results demonstrate that the proposed transversal navigation algorithm is suitable for polar UUV navigation.

Abstract: In recent years, a potential interest has been developed in exploring and enhancing the quality of underwater images. The captured underwater images often experience scattering and high levels of noise due to the properties of light transit within the water and the biotic movement that occurs inside the ocean bottom. Underwater cameras or devices were fitted inside the unmanned underwater vehicles (UUVs), autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs), ocean detector networks, etc to see the ocean bottom. Despite being a crucial detector for keeping an eye on underwater landscapes, modern underwater camera sensors or detectors contain a number of problems. Numerous solutions to the issues with conventional underwater photography have been put out during the last five years. With the help of the number of contributions and difficulties reported by more than 40 researchers in their research article, this study focused to mention the current underwater image processing methods. This article represents an overview of numerous underwater image-processing techniques utilized, including underwater picture de-scattering, underwater image colour refurbishment, and underwater image aspect evaluations. Also, the latest trends, problems, and challenges for creating and processing underwater image sensors were discussed.

*Agency for Defence Development, Jinhae, Korea**Graduate School of Korea Maritime University, Busan, Korea***Department of Ocean Engineering, Korea Maritime University, Busan, KoreaKEY WORDS: Cylindrical shell 원통형 구조물, High frequency vibration 고주파 진동, Excitation 가진, Noise 소음, Underwater vehicle 수중운동체ABSTRACT: Underwater vehicles such as UUVs (Unmanned Underwater Vehicles) and ROVs (Remotely Operated Vehicles) use sonar to detect their underwater environment or other underwater vehicles. The underwater vehicles designed recently have an electrical power system with high rotational speed. This system can generate high frequency vibra tions above 10 kHz, and these vibrations can cause bad (negativ e) effects on the performance of the sonar. In many previous investigations, nume rical analyses have been used for high frequency vibration prob lems. In this study, an experimental analysis was carried out, and a circular cylind rical shell was considered as the hull structure of an underwat er vehicle. Frequency transfer functions for the circular cylindrical shell were iden tified using an experimental vibration analysis in the air and in a fully-submerged condition. We compare the frequency transfer functions in the a ir and water to obtain hydro-elastic effects. It is found that the dynamic characteristics of the circular cylindrical shell are changed b y varying the response position.교신저자 박한일: 부산광역시 영도구 동삼 2동, 051-410-4326, hipark@hhu.ac.kr본 연구는 20011년 6월 개최된 한국해양과학기술협의회 공동학술대회에 발표된 논문을 근간으로 하고 있음을 밝힙니다 .

Underwater vehicles, and particularly unmanned underwater vehicles (UUVs), are becoming increasingly identified as safe and cost-effective solutions for a wide range of applications including environmental monitoring, facilities and vessel inspection, and exploration, often in hazardous environments or conditions. To address the growing need for UUV operations in hazardous environments, designs of unconventional, mission-specific platforms are being investigated in larger numbers. Operational performance requirements, such as precise hovering and very low speed maneuvering in currents and under waves for in-shore operations, demand a vehicle capable of rapid response to a changing environment by production of the proper time-varying balance of lift and thrust. In these highly dynamic flow fields, standard steady drag and moment curves are not valid models. Also, standard semi-empirical methods for coefficient estimation based on linearized Taylor Series expansions are not available for these systems, as neither full-scale nor model-scale performance data exist, except possibly in the case of torpedo-like hulls. This lack of existing data and modeling capability for unconventional systems led us to pursue the development of a high-fidelity direct computational method as a starting point to inform the designs and estimate performance in a highly nonlinear flow regime.