Junku Yuh

Design and Control of Autonomous Underwater Robots: A Survey

During the 1990s, numerous worldwide research and development activities have occurred in underwater robotics, especially in the area of autonomous underwater vehicles (AUVs). As the ocean attracts great attention on environmental issues and resources as well as scientific and military tasks, the need for and use of underwater robotic systems has become more apparent. Great efforts have been made in developing AUVs to overcome challenging scientific and engineering problems caused by the unstructured and hazardous ocean environment. In the 1990s, about 30 new AUVs have been built worldwide. With the development of new materials, advanced computing and sensory technology, as well as theoretical advancements, R&D activities in the AUV community have increased. However, this is just the beginning for more advanced, yet practical and reliable AUVs. This paper surveys some key areas in current state-of-the-art underwater robotic technologies. It is by no means a complete survey but provides key references for future development. The new millennium will bring advancements in technology that will enable the development of more practical, reliable AUVs.

Modeling and control of underwater robotic vehicles

With the increased utilization of remotely operated vehicles in subsea applications, the development of autonomous vehicles becomes highly desirable to enhance operator efficiency. The dynamic model of an untethered remotely operated underwater vehicle is presented, and an adaptive control strategy for such vehicles is described. The robustness of the control system with respect to nonlinear dynamic behavior and parameter uncertainties is investigated by computer simulation. The results show that the use of the adaptive control system can provide high performance of the vehicle in the presence of unpredictable changes in the dynamics of the vehicle and its environment. >

A neural net controller for underwater robotic vehicles

Results of a study on the application of neural networks to the control system of underwater robotic vehicles (URVs) are presented. The robustness of the control system with respect to nonlinear dynamic behavior and parameter uncertainties is investigated by computer simulation. The results show the feasibility of using unpredictable changes in the dynamics of the vehicle and its environment. >

Design of a semi-autonomous underwater vehicle for intervention missions (SAUVIM)

As the research in the autonomous underwater vehicle (AUV) field intensifies and the necessity of underwater robotic vehicles (URVs) increases, the requirements of an URV have expanded from simple fly-by missions to more complex, intervention missions. The Autonomous Systems Laboratory, Department of Mechanical Engineering, University of Hawaii is in the midst of designing and developing a semi-autonomous underwater vehicle for intervention missions (SAUVIM). The proposed open structure AUV possesses a fully functional manipulator, various mission sensors, and composite pressure vessels enclosed in a flooded composite fairing. The vehicle allows human-intervention from a land-based computer system capable of vehicle path-planning and monitoring.

Development of the Omni Directional Intelligent Navigator

The Autonomous Systems Laboratory is in the midst of developing an advanced underwater robotic technology test platform. The platform consists of the Omni-Directional Intelligent Navigator (ODIN) and the Integrated Graphic Workstation (IGW). ODIN is a six degree-of-freedom (dof) underwater vehicle with dual operational modes (autonomous and tethered) and a single dof mechanical manipulator. IGW is a real-time, 3-dimensional graphic monitoring, testing, and evaluation workstation. This paper presents ODINs mechanical and electrical specifications; its vehicle dynamics and depth control system; its recent simulation and experimental results; and IGWs specifications. >

An intelligent control system for remotely operated vehicles

The application of a neural network controller to remotely operated vehicles (ROVs) is described. Three learning algorithms for online implementation of a neural net controller are discussed with a critic equation. These control schemes do not require any information about the system dynamics except an estimate of the inertia terms. Selection of the number of layers in the neural network, the number of neurons in the hidden layer, initial weights for the network and the critic coefficient were done based on the results of preliminary tests. The performances of the three learning algorithms were compared by computer simulation. The effectiveness of the neural net controller in handling time-varying parameters and random noise is shown by a case study of the ROV system. >

Experimental study on adaptive control of underwater robots

The control of underwater robots presents a number of unique and formidable challenges. Underwater robot dynamics are highly nonlinear, coupled, and time-varying, and subject to hydrodynamic uncertainties and external disturbances such as current. Unlike land mobile robots, underwater robots cannot use GPS. Most popular underwater positioning sensors are sonar-based, such as long-base line. However, autonomous processing of sonar measurements is plagued by noise, drop-outs, missed detection, false reading, poor resolution, etc. The paper presents a new adaptive control of underwater robots with sonar-based position measurements. Experimental results show robustness of the control system in the presence of unmodelled dynamics and various noise.

Development of an underwater robot, ODIN-III

During the last decade, the first autonomous underwater robot of the Autonomous Systems Laboratory of the University of Hawaii, ODIN (Omni-Directional Intelligent Navigator) built in 1991 has produced a lot of valuable results in development and control methods [(S.K. Choi et al., July 1994), (Choi, S.K. et al., March 1995), (S.K. Choi et al., April 1996), (Yang, K.C. et al., September 1999), (J. Yuh et al., 2000)]. Recently, ODIN was born again in the 3rd generation with unique features under recent technologies such as abundant system resources owing to a PC104+, new vehicle system software architectures with an object-oriented concept and its implementation, a graphical user interface and an independent algorithm module using a dynamic linking library (DLL) based on the Windows operating system. These give us an ideal environment for developing various algorithms which are needed for developing an advanced underwater robotic vehicle. This paper describes details of the development of ODIN-III and presents initial experimental results for fine motion control.

Design of omni-directional underwater robotic vehicle

Underwater robotic vehicles have been attractive to many applications. Among potential applications of these vehicles include fishery, underwater pollution monitoring, and waste cleaning and handling in the ocean as well as nuclear sites. Over the last decade, there has been increasing R&D effort toward more advanced and intelligent underwater vehicles in support of a variety of applications. In the Autonomous Systems Laboratory, an omni-directional intelligent navigator (ODIN) which has dual (autonomous/remote) operational modes and a mechanical manipulator, was designed as a part of the research in developing a real-time 3D graphic, integrated test platform for advanced vehicle technologies. RSI Research Ltd. manufactured the first model which is described in this paper.<<ETX>>

Fault-tolerant system design of an autonomous underwater vehicle ODIN: An experimental study

This paper describes the design and implementation of a fault-tolerant system for Omni-Directional Intelligent Navigator (ODIN), a six-degree-of-freedom autonomous underwater vehicle (AUV) designed at the University of Hawaii. A fault-tolerant system consists of three areas: fault detection, fault isolation and fault accommodation. Each area is described, and methods discussed in the literaturearebriefly reviewed. The presented design focuses on the thruster (or actuator) and sensor system failures in an AUV. Experimental results show that the presented approach is practical and effective when tolerable failures in actuators and sensors occur. This methodology and concept can be extended to fault-tolerant system design for various AUVs with hardware redundancy.