in the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. in this study, hydrodynamic coefficients of an autonomous un...

We present a system for autonomous underwater navigation as implemented on a Nekton Ranger autonomous underwater vehicle, AUV. This is one of the rst implementations of a practical application for simultaneous localization and mapping on an AUV. Besides being an application of real-time SLAM, the implemtation demonstrates a novel data fusion solution where data from 7 sources are fused at di er...

A neural network based robust control system design for the yaw angle of autonomous underwater vehicle (AUV) is presented in this paper. Two types of control structure were used to control prescribed trajectories of an AUV. The results of the simulation showed that the proposed neural network based robust control system has superior performance in adapting to large random disturbances such as w...

This paper focuses on a critical component of the situational awareness (SA), the neural control of autonomous constant depth flight of an autonomous underwater vehicle (AUV). Autonomous constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth...

Maintaining accurate localization of an autonomous underwater vehicle (AUV) is difficult because electronic signals such as GPS are highly attenuated by water making established land-based localization systems, such as GPS, useless underwater. Instead we propose an alternative approach which integrates position information of other vehicles to reduce the error and uncertainty of the on-board po...

This paper addresses the issue of guidance and control of an autonomous underwater vehicle (AUV) for a cable tracking problem. A linear quadratic Gaussian controller with loop transfer recovery (LQG/LTR) is developed because of its strong robustness properties. The vehicle is guided towards the target using a combination of different guidance algorithms. The vehicle speed is used to formulate t...

In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous un...

This paper explores the intersection of two fields of research: autonomous underwater vehicles (AUVs), and archaeology in the deep sea. Archaeology in the deep sea poses a range of difficult, interesting problems for autonomous underwater vehicles. These include broad area sonar searches, target identification, and precision survey. Broad area sonar searches for archaeology have requirements si...

An adaptive neural network controller for autonomous underwater vehicles (AUVs) is presented in this paper. The AUV model is highly nonlinear because of many factors, such as hydrodynamic drag, damping, and lift forces, Coriolis and centripetal forces, gravity and buoyancy forces, as well as forces from thruster. In this regards, a nonlinear neural network is used to approximate the nonlinear u...

This article provides a general overview of the autonomous underwater vehicle (AUV) research thrusts being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL’s research centers on improving AUV autonomy via algorithmic advancements in environmentally based perceptual feedback for real-time mapping, navigation, and control. Our three maj...