Semi-autonomous Underwater Vehicle Research Articles

Visual-Aided Shared Control of Semi-Autonomous Underwater Vehicle for Efficient Underwater Grasping

Human intelligence has the advantage for making high-level decisions in the remote control of underwater vehicles, while autonomous control is superior for accurate and fast close-range pose adjustment. Combining the advantages of both remote and autonomous control, this paper proposes a visual-aided shared-control method for a semi-autonomous underwater vehicle (sAUV) to conduct flexible, efficient and stable underwater grasping. The proposed method utilizes an arbitration mechanism to assign the authority weights of the human command and the automatic controller according to the attraction field (AF) generated by the target objects. The AF intensity is adjusted by understanding the human intention, and the remote-operation command is fused with a visual servo controller. The shared controller is designed based on the kinematic and dynamic models, and model parameter uncertainties are also addressed. Efficient and stable control performance is validated by both simulation and experiment. Faster and accurate dynamic positioning in front of the target object is achieved using the shared-control method. Compared to the pure remote operation mode, the shared-control mode significantly reduces the average time consumption on grasping tasks for both skilled and unskilled operators.

Towards remote surveillance of marine pests: A comparison between remote operated vehicles and diver surveys

Early detection of marine invasive species is key for mitigating and managing their impacts to marine ecosystems and industries. Human divers are considered the gold standard tool for detecting marine invasive species, especially when dive teams are familiar with the local biodiversity. However, diver operations can be expensive and dangerous, and are not always practical. Remote operated vehicles (ROVs) can potentially overcome these limitations, but it is unclear how sensitive they are compared to trained divers for detecting pests. We assessed the sensitivity and efficiency of ROVs and divers for detecting marine non-indigenous species (NIS), including the potential for automated detection algorithms to reduce post-processing costs of ROV methods. We show that ROVs can detect comparable assemblages of invasive species as divers, but with lower detection rates (0.2 NIS min-1) than divers (0.5 NIS min-1) and covered less seafloor than divers per unit time. While small invertebrates (e.g., skeleton shrimp Caprella mutica) were more easily detected by divers, the invasive goby Acentrogobius pflaumii was only detected by the ROV. We show that implementation of computer vision algorithms can provide accurate identification of larger biofouling organisms and reduce overall survey costs, yet the relative costs of ROV surveys remain almost twice that of diver surveys. We expect that as ROV technologies improve and investment in autonomous and semi-autonomous underwater vehicles increases, much of the current inefficiencies of ROVs will be mitigated, yet practitioners should be aware of limitations in taxonomic resolution and the strengths of specialist diver teams.

Development stages of a semi-autonomous underwater vehicle experiment platform

The design of underwater unmanned vehicles is an interdisciplinary study that includes several fields, such as computational fluid dynamics, modeling and control of systems, robotics, image processing, and electronic card design. The operational cost of such vehicles is high because it is dependent on variable fluid properties like salinity and high pressure while its’ mobility must be resistant to environmental conditions such as undersea. The study describes an operating platform, called Lucky Fin, on which the students can develop various control algorithms and can test and extract hydrodynamic parameters of the underwater vehicle. The platform consists of an underwater vehicle and two testing tanks. The control card, the user control program interface, and a manipulator’s arm are designed to be used for a series of control applications such as depth, heading, target tracking, and capturing. The results of several tests are illustrated in this article.

Underwater robots provide similar fish biodiversity assessments as divers on coral reefs

AbstractCoral reefs are under increasing threat, and the loss of reef‐associated fishes providing valuable ecosystem services is accelerating. The monitoring of such rapid changes has become a challenge for ecologists and ecosystems managers using traditional approaches like scuba divers performing underwater visual censuses (UVC) or diver operated video recording (DOV). However, the use of small, low‐cost robots could help tackle the challenge of such monitoring, provided that they perform at least as well as diver‐based methods. To address this question, tropical fish assemblages from 13 fringing reefs around Mayotte Island (Indian Ocean) were monitored along 50 m‐long transects using stereo videos recorded by a semi‐autonomous underwater vehicle (SAUV) and by a scuba diver (Diver Operated stereo Video system, DOV). Differences between the methods were tested for complementary fish assemblage metrics (species richness, total biomass, total density, Shannon diversity and Pielou evenness) and for the number and size of nine targeted species. SAUV recorded on average 35% higher biomass than DOV which in turn recorded on average 12% higher species richness. Biomass differences were found to be due to SAUV monitoring larger fishes than DOV, a potential marker of human‐related fish avoidance behaviour. This study demonstrates that SAUV provides accurate metrics of coral reef fish biodiversity compared to diver‐based procedures. Given their ability to conduct video transects at high frequency, 100 m depth range and at a moderate cost, SAUV is a promising tool for monitoring fish assemblages in coral reef ecosystems.

Interview with Junku Yuh, Principal Investigator of the SAUVIM Project [History

The following article is an interview conducted for IEEE Robotics and Automation Magazine (RAM) with Dr. Junku Yuh, director of the Robotics and Media Institute at the Korea Institute of Science and Technology, Seoul. Dr. Yuh was the principal investigator of the Semiautonomous Underwater Vehicle for Intervention Missions (SAUVIM) project, which achieved an important milestone in underwater robotics’ history: the first demonstration of autonomous underwater floating manipulation.

High Resolution Orthomosaics of African Coral Reefs: A Tool for Wide-Scale Benthic Monitoring

Coral reefs play a key role in coastal protection and habitat provision. They are also well known for their recreational value. Attempts to protect these ecosystems have not successfully stopped large-scale degradation. Significant efforts have been made by government and research organizations to ensure that coral reefs are monitored systematically to gain a deeper understanding of the causes, the effects and the extent of threats affecting coral reefs. However, further research is needed to fully understand the importance that sampling design has on coral reef characterization and assessment. This study examines the effect that sampling design has on the estimation of seascape metrics when coupling semi-autonomous underwater vehicles, structure-from-motion photogrammetry techniques and high resolution (0.4 cm) underwater imagery. For this purpose, we use FRAGSTATS v4 to estimate key seascape metrics that enable quantification of the area, density, edge, shape, contagion, interspersion and diversity of sessile organisms for a range of sampling scales (0.5 m × 0.5 m, 2 m × 2 m, 5 m × 5 m, 7 m × 7 m), quadrat densities (from 1–100 quadrats) and sampling strategies (nested vs. random) within a 1655 m2 case study area in Ponta do Ouro Partial Marine Reserve (Mozambique). Results show that the benthic community is rather disaggregated within a rocky matrix; the embedded patches frequently have a small size and a regular shape; and the population is highly represented by soft corals. The genus Acropora is the more frequent and shows bigger colonies in the group of hard corals. Each of the seascape metrics has specific requirements of the sampling scale and quadrat density for robust estimation. Overall, the majority of the metrics were accurately identified by sampling scales equal to or coarser than 5 m × 5 m and quadrat densities equal to or larger than 30. The study indicates that special attention needs to be dedicated to the design of coral reef monitoring programmes, with decisions being based on the seascape metrics and statistics being determined. The results presented here are representative of the eastern South Africa coral reefs and are expected to be transferable to coral reefs with similar characteristics. The work presented here is limited to one study site and further research is required to confirm the findings.

Development of a master controller for a 3-link dual-arm underwater robot

Master-slave system is a vital technique for controlling robot motions. An intuitive master controller enables precise and easy control of robot, especially for underwater robotics applications. Most of the commercially available master-slave systems are very complex and expensive, and operators need to receive extensive training before being able to correctly operate the robot. This paper addresses these problems by introducing a simple and intuitive master controller for an experimental semi-autonomous underwater vehicle equipped with 3-link dual-arm. The master controller includes a vehicle main master controller and two units of 3-link manipulator master controller. Moreover, each end-tip of the manipulator master controller is attached with a vehicle sub-master controller that consists of a joystick and tactile switches. These sub-master controllers are designed to control the position and attitude of the vehicle. The ability to simultaneously control two units of 3-link dual-arm and the position and attitude of the vehicle is the uniqueness of the proposed controller. In this work, the design of the developed master controller and the structure of a unilateral master-slave system are presented. The usefulness of the master controller is verified through experiment on controlling an actual dual-arm underwater robot to catch a target object in underwater environment.

Towards a Framework for Human Factors in Underwater Robotics

This paper presents a study identifying the human-, robot-, task-, and environmental-related factors that impact the feasibility and usability of semi Autonomous Underwater Vehicles (sAUVs) from a human factors perspective. A multi-method approach was utilized. First, a subject matter expert (SME) interview was used to analyze video data of operators interacting with sAUVs. The results suggest considerations for the capabilities and limitations of the human and robot, in relation to the dynamic demands of the task and environment. A preliminary human factors conceptual model to depict and categorize these components was proposed. Next, a questionnaire was administered to sAUV roboticists (N=15) that assessed their perceptions related to the level of challenge associated to each of the factors identified in the model. The data suggest that all of the factors identified in our conceptual model are, in fact, challenging. In particular, our data suggest that situation awareness, communication, task complexity, visibility, and the robot’s user interface were some of the most challenging variables in sUAV operation.

2A1-C09 Development of a semi-autonomous underwater robot equipped with 3-link dual-arm

We have been developing a semi-autonomous underwater vehicle (semi-AUV) equipped with 3-link dual-arm for underwater intervention tasks. In this work, brief description of the developed semi-AUV and a single-person operated master controller that can simultaneously operate the semi-AUV and dual-arm is described. Furthermore, preliminary experimental results showing the effectiveness of the master controller in controlling the semi-AUV is presented.

Introduction to Autonomous Manipulation: Case Study with an Underwater Robot, SAUVIM [On the Shelf

This book examines the market for disaster robots and the technology's ability to operate in unstructured environments. It delves into this challenging topic, presenting solutions through a careful case study in underwater robotics, a project called the semiautonomous underwater vehicle for intervention missions (SAUVIM).

Power Distribution in Propulsion System of Semiautonomous Underwater Vehicle

This paper presents methods of power distribution in propulsion system of a small torpedo-shape underwater vehicle maneuverable in three dimensions. It concentrates on finding an optimal thrust allocation among thrusters for demanded values of propulsive forces and moments. The proposed approach is directed towards obtain high propulsive efficiency necessary to realize required mission. Two described methods allow minimizing the propulsion system’s power consumption necessary to produce required thrusts.

Real-time center of buoyancy identification for optimal hovering in autonomous underwater intervention

This work addresses the problem of optimal positioning for an intervention AUV, minimizing the energy consumption and improving the stability in orientation. During a generic intervention task, the vehicle is generally maintained in a hovering configuration, thus requiring a 6 DOF control of the vehicle positioning. The choice of roll and pitch, if done arbitrarily, can severely impact the power efficiency of the vehicle, especially in heavy systems, since the center of buoyancy (COB) may not be necessarily aligned over the center of mass (COM). This approach uses an Extended Kalman Filter (EKF) to identify the location of the center of buoyancy relative to the center of mass, thus allowing to compute the working orientation that maintains the COB vertically aligned above the COM. The EKF is implemented online and hence is able to detect movements of the COB due for example to ballast operations. This algorithm has been firstly implemented in simulation and then successfully validated with the SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions) autonomous underwater vehicle. With its weight of about 4 tons, this testbed is an optimal platform for validating the precision of the filter, since a very small variation of the target pitch and roll results in a large restoring torque.

AUV Guidance and Navigation using Intelligent Control

The design and implementation of a control layer architecture used to control the motions of a Semi Autonomous Underwater Vehicle (SAUV) is focused and presented. At first, the main functionalities required for navigation, guidance and collision avoidance during missions of marine robots are drafted to facilitate the understanding of the whole design process. After that, a set of rules are created, seeking to guarantee the consistency and correctness of the control system operation. A modular topology is employed to establish this set of rules, i.e. input-output relationships are clearly defined at each execution level, ruled through constraints established through an algorithm based on fuzzy logic. The control system itself is subdivided into three layers. Extensive simulation studies are then performed using the configuration of a vehicle under construction. The main advantages of the proposed navigation control architecture lies in its simplicity, modularity and flexibility, leading to a high performance of the control system.

Optimal Control System for a Semi-Autonomous Underwater Vehicle

This work presents a proposal of Navigation and Control System (NCS) to a Semi-Autonomous Underwater Vehicle (SAUV) under construction at the University of SÃo Paulo (USP). Three horizontal Degrees-of-Freedom (DoF) are controlled to track reference trajectories determined by a support station, responsible for the guidance of the vehicle. The NCS is basically a Linear Quadratic (LQ) Trajectory Tracker fed by an estimated state vector, with some other interesting functionalities included. All results were obtained by computational simulations with a nonlinear model of the plant of the SAUV driven by the NCS.

Underwater autonomous manipulation for intervention missions AUVs

Many underwater intervention tasks are today performed using manned submersibles or remotely operated vehicles in teleoperation mode. Autonomous underwater vehicles are mostly employed in survey applications. In fact, the low bandwidth and significant time delay inherent in acoustic subsea communications represent a considerable obstacle to remotely operate a manipulation system, making it impossible for remote controllers to react to problems in a timely manner. Nevertheless, vehicles with no physical link and with no human occupants permit intervention in dangerous areas, such as in deep ocean, under ice, in missions to retrieve hazardous objects, or in classified areas. The key element in underwater intervention performed with autonomous vehicles is autonomous manipulation. This is a challenging technology milestone, which refers to the capability of a robot system that performs intervention tasks requiring physical contacts with unstructured environments without continuous human supervision. Today, only few AUVs are equipped with manipulators. SAUVIM (Semi Autonomous Underwater Vehicle for Intervention Mission, University of Hawaii) is one of the first underwater vehicle capable of autonomous manipulation. This paper presents the solutions chosen within the development of the system in order to address the problems intrinsic to autonomous underwater manipulation. In the proposed approach, the most noticeable aspect is the increase in the level of information transferred between the system and the human supervisor. We describe one of the first trials of autonomous intervention performed by SAUVIM in the oceanic environment. To the best knowledge of the authors, no sea trials in underwater autonomous manipulation have been presented in the literature. The presented operation is an underwater recovery mission, which consists in a sequence of autonomous tasks finalized to search for the target and to securely hook a cable to it in order to bring the target to the surface.

반 자율 무인 잠수정의 개발

This paper is mainly concerned with the development of the semi-autonomous underwater vehicle (SAUV). Underwater vehicles are affected by external disturbances due to the sea conditions such as currents and waves when it is performing various missions In this paper we present a design scheme of the SAUV system with mathematical models. Also. we present a control system including motion control of motors and main controller and a communication based on CAN method for interrelated control between the controllers and actuators.

A hierarchical real-time control architecture for a semi-autonomous underwater vehicle

This paper describes a real-time control architecture for Dual Use Semi-Autonomous Underwater Vehicle (DUSAUV), which has been developed at Korea Research Institute of Ships and Ocean Engineering (KRISO) for being a test-bed of development of underwater navigation and manipulator technologies. DUSAUV has three built-in computers, seven thrusters for six DOF motion control, one 4-function electric manipulator, one ballasting motor, built-in power source, and various sensors. A supervisor control system with GUI and a multi-purpose joystick is mounted on the surface vessel and communicates with vehicle through a fiber optic link. Furthermore, QNX, one of real-time operating system, is ported on the built-in control and navigation computers for real-time control purpose, while Microsoft OS product is ported in the supervisor computer for GUI programming convenience. A hierarchical control architecture, which consists of application layer, real-time layer and physical layer, has been developed for efficient control system of above complex underwater robotic system. The experimental results with implementation of the layered control architecture for various motion control of DUSAUV in an ocean engineering basin of KRISO is also presented.

Fuzzy-Logic Based Navigation of Underwater Vehicles

A fuzzy logic based general purpose modular control architecture is presented for underwater vehicle autonomous navigation, control and collision avoidance. Three levels of fuzzy controllers comprising the sensor fusion module, the collision avoidance module and the motion control module are derived and implemented. No assumption is made on the specific underwater vehicle type, on the amount of a priori knowledge of the 3-D undersea environment or on static and dynamic obstacle size and velocity. The derived controllers account for vehicle position accuracy and vertical stability in the presence of ocean currents and constraints imposed by the roll motion. The main advantage of the proposed navigation control architecture is its simplicity, modularity, expandability and applicability to any type of autonomous or semi-autonomous underwater vehicles. Extensive simulation studies are performed on the NPS Phoenix vehicle whose dynamics have been modified to account for roll stability.

Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions

The need for autonomous underwater vehicles (AUVs) for intervention missions becomes greater as they can perform underwater tasks requiring physical contacts with the underwater environment, such as underwater plug-in/plug-out, construction and repair, cable streaming, mine hunting, munitions retrieval, and scientific sampling. This paper describes a semi-autonomous underwater vehicle for intervention missions that has multiple on-board CPUs, redundant sensors and actuators, on-board power source and a robotic manipulator for dextrous underwater performance. Such a complex robotic vehicle system requires advanced control software architecture for on-board intelligence with a wide range of sensors and actuators to carry out required missions. In this paper, AUV control architectures are reviewed and a sensor data bus based control architecture (SDBCA) is presented. SDBCA is a modified hierarchical architecture that offers good controllability and stability while sensor data bus increases flexibility of system design, making it possible to have a prompt response from high-level control with respect to low-level sensor data. The overall sensor input mechanism of SDBCA becomes similar to the sensor input mechanism of subsumption architecture.

Real-Time Control Architecture for Sauvim

This paper provides an overview of hardware and software architecture of SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions) which has been developed at the Autonomous Systems Laboratory (ASL). Unlike other autonomous underwater vehicles (AUVs), SAUVIM is equipped with an electric motor-driven dexterous robotic manipulator for underwater tasks requiring physical contacts with underwater objects. The overall vehicle-manipulator system becomes a high degrees-of-freedom multi-body nonlinear dynamic system. To effectively control this complex robotic system, distributed real-time hardware architecture and modified hierarchical software architecture with Sensor Data Bus (SDB) were used. The SDB makes it possible to get a prompt response from high-level control with respect to low-level sensor data. SAUVIM Task Description Language (STDL) was also developed to increase the flexibility of the vehicle tasks. Using STDL, any modification of control software is not required for various tasks. The user can also easily describe a task with various sensor data and handle multiple actuators.