Development of dam inspection robot with negative pressure effect plate

This paper describes the development of an underwater robot that performs visual inspection while making mechanical contact with a dam surface by a pulling force generated from thrusters with negative pressure effect plates. In general, small and lightweight remotely operated vehicles (ROVs) have low‐power thrusters. Their positioning performance is inferior with respect to external disturbances. Moreover, it is difficult for untrained operators to control the ROV position to check and inspect dams visually. A negative pressure effect plate attached to a thruster produces negative pressure that maintains mechanical contact between the robot and a dam wall surface and ensures stable robot motion on a dam surface to acquire clear continuous images. As described herein, we theoretically investigate the negative pressure effect plate characteristics and experimentally measure the force generated by the pressure difference. Results show that the force of a thruster with the effect plate is five times greater than the nominal thrust force provided by the thruster alone. Based on those results, we designed and developed the underwater robot with the negative pressure effect plates for dam inspection. Moreover, we conducted an experiment in a water tank and a field test at Shorenji Dam, Mie‐prefecture, Japan. The experimentally obtained results indicated that the negative pressure effective plate is effective at generating sufficient force and at realizing stable robot motion on the dam surface. Results demonstrate that the developed robot acquired clear images of the dam surface continuously with no sophisticated operator or controller.     

A comparative study of control techniques for an underwater flight vehicle

Unmanned, underwater vehicles have been developed considerably in recent years. Remotely operated vehicles (ROVs) are increasingly used for routine inspection and maintenance tasks but have a range that is limited by the umbilical cable. For long range operations, such as oceanographic exploration and surveying, autonomous underwater vehicles (AUVs) are emerging which haveon-board power and are equipped with advanced control capabilities to carry out tasks with the minimum of human intervention. AUVs typically resemble torpedoes in that mosthave control surfaces and a single propulsion unit, and must move forwards to manoeuvre. Such vehicles are called flight vehicles. This paper describes techniques which are candidates for control of a flight AUV and identifies controllers used on some existing vehicles. Since underwater vehicle dynamics are nonlinear, fuzzy logic and sliding mode control were felt to have promise for autopilot application due to their potential robustness. Following development using a comprehensive simulation programme, the controllers were tested using the experimental vehicle, Subzero II, and their performance compared with that of a classical linear controller. The relative merits of the methods for practical implementation are discussed.     

An experimental investigation into the fault-tolerant control of an autonomous underwater vehicle

Autonomous underwater vehicles (AUVs) are expected to function in an unstructured underwater environment. One of the main requirements for effective operation in such an environment is to accommodate faults. In this paper, we have investigated a new approach to the allocation of thruster forces of an autonomous underwater vehicle under thruster faults. Generally, an AUV is equipped with more thrusters than what is minimally required to produce the desired motion. The proposed framework exploits the excess number of thrusters to accommodate thruster faults during operation. First, a redundancy resolution scheme is presented that considers the presence of excess number of thrusters along with any thruster faults and determines the reference thruster forces to produce the desired motion. These reference thruster forces are then utilized in the thruster controller to generate the required motion. This approach resolves the thruster redundancy in the Cartesian space and allows the AUV to track the task-space trajectories with asymptotic reduction of the task-space errors. Results from actual underwater experiments are provided to demonstrate the viability of the proposed scheme.     

Multisensor visualization for underwater archaeology

The problems particular to underwater archaeology are discussed. The underwater archaeology study of three sunken ships is then described. They are the USS Monitor, Hamilton and Scourge. Future prospects with respect to improved technology are indicated. From depths prohibitive to human divers, remotely operated vehicles (ROVs) send back acoustic and optical data to archaeologists safe and comfortable aboard ship. Sonars give the big picture, and acoustic data can be processed to extract spatial information: shape and relative placement of artifacts. Still cameras and video document fine-scale features, allowing an archaeologist to identify and date underwater relics. New computational and graphics technologies afford scientists and engineers a visual means of digesting the massive information flow from state-of-the-art ROVs     

A cooperative architecture for target localization using multiple AUVs

A recent concern in marine robotics is to consider the deployment of fleets of autonomous underwater vehicles (AUVs) and autonomous surface vehicles (ASVs). Multiple vehicles with heterogeneous capabilities have several advantages over a single vehicle system, and in particular the potential to accomplish tasks faster and better than a single vehicle. This paper addresses in this context the problem of underwater targets localization. A systematic and exhaustive coverage strategy is not efficient in terms of exploration time: it can be improved by making the AUVs share their information to cooperate, and optimize their motions according to the state of their knowledge on the target localization. We present techniques to build environment representations on the basis of which adaptive exploration strategies can be defined, and define an architecture that allows information sharing and cooperation between the AUVs. Simulations are carried out to evaluate the proposed architecture and the adaptive exploration strategies.     

基于逆模型的混合驱动水下滑翔机垂直面控制

混合驱动水下滑翔机（Hybrid-driven underwater gliders ,简称HDUGs)是集无人自治水下机器人（Automomous Underwater Vehicles ,简称 AUVs）和水下滑翔机（Autonomous Underwater Gliders,简称 AUGs）于一体的新型水下机器人。由于HDUGs是非线性、强耦合,且受到海流、结构不确定等因素的影响,为了克服这些问题,针对混合驱动水下机器人工作在混合模式下,对其垂直面提出了一种基于逆模型和滑模控制的非线性控制方法,该方法将原始系统解耦为两个单入单出的线性系统,仿真结果证明了该方法具有良好的控制性能,而且对外界扰动具有一定的鲁棒性。     

Motion and force control with a nonlinear force error filter for underwater vehicle-manipulator systems

This paper deals with a control scheme for autonomous underwater robots equipped with manipulators. Several motion and force controllers have been developed. Most of them were designed in disregard of the dynamics of marine thrusters to develop a controller with a simple structure. However, the robot body propelled by thrusters generally has a considerably slower time response than the manipulator driven by electrical motors. Therefore, it may be difficult to construct a high-gain feedback control system to achieve a good control performance, because the high gain may excite the slow thruster dynamics ignored in the controller design, and the excitation will degrade the control performance. In this paper, we develop a motion and force controller for mathematical models with the dynamics of thrusters. It includes a nonlinear force error filter which allows us to construct a stable motion and force control system. To investigate its control performance, we conducted numerical simulations for comparing the proposed control scheme with an existing control scheme designed in disregard of the thruster dynamics. Simulation results demonstrate the usefulness of the proposed controller.     

Naval Mine Countermeasure Missions

Undersea operations using autonomous underwater vehicles (AUVs) provide a different and in some ways a more challenging problem than tasks for unmanned aerial vehicles and unmanned ground vehicles. In particular, in undersea operations, communication windows are restricted, and bandwidth is limited. Consequently, coordination among agents is correspondingly more difficult. In traditional approaches, a central planner initially assigns subtasks to a set of AUVs to achieve the team goal. However, those initial task assignments may become inefficient during real-time execution because of the real-world issues such as failures. Therefore, initial task allocations are usually subject to change if efficiency is a high concern. Reallocations are needed and should be performed in a distributed manner. To provide such flexibility, we propose a distributed auction-based cooperation framework, distributed and efficient multirobot-cooperation framework (DEMiR-CF), which is an online dynamic task allocation (reallocation) system that aims to achieve a team goal while using resources effectively. DEMiR-CF, with integrated task scheduling and execution capabilities, can also respond to and recover from real-time contingencies such as communication failures, delays, range limitations, and robot failures.     

基于BP神经网络的水下机器人推进器故障辨识算法

常规无人水下机器人推进器故障诊断中,均假设推进器处于几种固定故障模式,这与实际推进器故障情况有较大差别。该文将信息融合故障诊断技术引入推进器拥堵故障在线辨识之中,提出基于BP误差反传神经网络(Error Back Propagation Network)信息融合在线故障辨识模型,将水下机器人控制信号和故障情形下的方向偏转率作为BP神经网络融合模型输入,其输出即为反应推进器故障大小的拥堵系数,不仅提高了故障辨识精度,而且对连续不确定故障实现有效辨识。     

Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.     

Effective Turning Motion Control of Internally Actuated Autonomous Underwater Vehicles

This paper presents a novel roll mechanism and an efficient control strategy for internally actuated autonomous underwater vehicles (AUVs). The developed control algorithms are tested on Michigan Tech’s custom research glider, ROUGHIE (Research Oriented Underwater Glider for Hands-on Investigative Engineering), in a controlled environment. The ROUGHIE’s design parameters and operational constraints were driven by its requirement to be man portable, expandable, and maneuverable in shallow water. As an underwater glider, the ROUGHIE is underactuated with direct control of only depth, pitch, and roll. A switching control method is implemented on the ROUGHIE to improve its maneuverability, enabling smooth transitions between different motion patterns. This approach uses multiple feedforward-feedback controllers. Different aspects of the roll mechanism and the effectiveness of the controller on turning motion are discussed based on experimental results. The results illustrate that the ROUGHIE is capable of achieving tight turns with a radius of 2.4 meters in less than 3 meters of water, or one order of magnitude improvement on existing internally actuated platforms. The developed roll mechanism is not specific to underwater gliders and is applicable to all AUVs, especially at lower speeds and in shallower water when external rudder is less effective in maneuvering the vehicle.     

Adaptive autonomous underwater vehicles for littoral surveillance

Autonomous underwater vehicles (AUVs) have gained more interest in recent years for military as well as civilian applications. One potential application of AUVs is for the purpose of undersea surveillance. As research into undersea surveillance using AUVs progresses, issues arise as to how an AUV acquires, acts on, and shares information about the undersea battle space. These issues naturally touch on aspects of vehicle autonomy and underwater communications, and need to be resolved through a spiral development process that includes at sea experimentation. This paper presents a recent AUV implementation for active anti-submarine warfare tested at sea in the summer of 2010. On-board signal processing capabilities and an adaptive behavior are discussed in both a simulation and experimental context. The implications for underwater surveillance using AUVs are discussed.     

Synchronization of multiple autonomous underwater vehicles without velocity measurements

In this paper,we investigate the synchronization control of multiple autonomous underwater vehicles (AUVs),considering both state feedback and output feedback cases.Treating multiple AUVs as a graph,we define the tracking error of each AUV with both its own tracking error and the relative position errors with respect to its neighbors taken into account.Lyapunov analysis is used to derive the control law for each AUV.For the output feedback case,a passive filter is used to compensate for the unknown relative velocity errors among AUVs,and an observer is employed to estimate the velocity of the AUV itself.Rigid mathematical proof is provided for the proposed algorithms for both state feedback and output feedback cases.Simulations are provided to demonstrate the effectiveness of the proposed approach.It is shown that,the synchronization error is smaller in the case of considering the relative errors between AUVs than in the case of considering the tracking error of the single AUV only.     

Navigation of an AUV for investigation of underwater structures

There is a great demand for autonomous underwater vehicles (AUVs) to investigate artificial underwater structures such as piles and caissons in harbours, and risers and jackets of deep-sea oilfields. This paper proposes an autonomous investigation method of underwater structures using AUVs that is implemented by initially detecting the target objects, localizing them, then approaching them by taking video images while closely tracing their shape. A laser ranging system and a navigation method based on the relative position with respect to the target objects are introduced to realize this behaviour.     

Underwater guidance of distributed autonomous underwater vehicles using one leader

Consider the case where autonomous underwater vehicles (AUVs) are deployed to monitor a 3D underwater environment. This paper tackles the problem of guiding all AUVs to the destination while not colliding with a priori unknown 3D obstacles. Suppose that among all AUVs, only the leader AUV has an ability of locating itself, while accessing a destination location. A follower, an AUV that is not a leader, has no sensors for locating itself. Every follower can only measure the relative position of its neighbor AUVs utilizing its sonar sensors. Our paper addresses distributed controls, so that multiple followers track the leader while preserving communication connectivity. We design controls, so that all AUVs reach the destination safely, while maintaining connectivity in cluttered 3D environments. To the best of our knowledge, our article is novel in developing 3D underwater guidance controls, so that all AUVs equipped with sonar sensors are guided to reach a destination in a priori unknown cluttered environments. MATLAB simulations are used to validate the proposed guidance scheme in underwater environments with many obstacles.     

Minimum Speed Seeking Control for Nonhovering Autonomous Underwater Vehicles

Most autonomous underwater vehicles (AUVs) are propelled by a single thruster, use elevators and rudders as control surfaces, and are torpedo‐shaped. Furthermore, they are positively buoyant to facilitate recovery during an emergency. For this class of nonhovering AUVs, there is a minimum speed at which the AUV must travel for stable depth control. Otherwise, the extra buoyancy will bring the AUV up to the surface when the fin loses its effectiveness at low speeds. Hence, we develop a novel algorithm such that the AUV is automatically controlled to travel at its minimum speed while maintaining a constant depth. This capability is important in a number of practical scenarios, including underwater loitering with minimum energy consumption, underwater docking with minimum impact, and high‐resolution sensing at minimum speed. First, we construct a depth dynamic model to explain the mechanism of the minimum speed, and we show its relationship with the buoyancy, the righting moment, and the fin's effectiveness of the AUV. Next, we discuss the minimum speed seeking problem under the framework of extremum seeking. We extend the framework by introducing a new definition of steady‐state mapping that imposes new structure on the seeking algorithm. The proposed algorithm employs a fuzzy inference system, which is driven by the real‐time measurements of pitch error and elevator deflection. The effectiveness of the algorithm in seeking the minimum speed is validated in both simulations and field experiments.     

Dynamic positioning of remotely operated underwater vehicles

The paper describes an automatic dynamic positioning system for remotely operated underwater vehicles (ROVs) using a mechanical passive arm for position measurement that is suitable for inspection and intervention tasks requiring precise positioning. Good dynamic performance in tracking was also attained, particularly with the variable structure model reference adaptive control strategy     

基于多AUV间任务协作的水下多目标探测机制

利用自主式水下航行器（Autonomous Underwater Vehicle, AUV）对水下多目标进行协同探测是目前海洋技术领域的研究热点。本文主要研究在水下三维区间内的多AUV任务分配与协作探测机制,建立了以每个AUV能量耗费与能耗均衡为约束条件的水下三维空间中的多旅行商（Multiple Traveling Salesman Problem, MTSP）问题模型,利用遗传算法（Genetic Algorithm, GA）对该NP-Complete问题进行启发式求解,同时设计了考虑巡航总路径及访问目标数的适应度函数以提高多AUV间的能耗均衡性,实现多个AUV对多个水下目标的优化协同探测。最后本文利用Matlab R2014a软件对多AUV任务协作与多目标探测机制进行了仿真,仿真结果验证了该方法能够均衡多AUV多目标探测问题的能量消耗,进而提高巡航速度和生命周期。     

Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

The underwater swimming manipulator (USM) is a snake‐like, multi‐articulated, underwater robot that is equipped with thrusters. One of the main purposes of the USM is to act like an underwater floating base manipulator. As such, it is essential to achieve good station‐keeping and trajectory tracking performance for the USM by using the thrusters and by using the joints to attain the desired position and orientation of the head and tail of the USM. In this ‘paper, we propose a sliding mode control (SMC) law, specifically the super‐twisting algorithm with adaptive gains, for the trajectory tracking of the USM's centre of mass. A higher‐order sliding mode observer is proposed for state estimation. Furthermore, we show the ultimate boundedness of the tracking errors. We demonstrate the applicability of the proposed control law and show that it leads to better performance than a linear PD‐controller.