Download or read book Exploring the Utility of the REMUS Autonomous Underwater Vehicle for Search classify map Missions written by Daniel E. Sgarioto and published by . This book was released on 2011 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Minefield Search and Object Recognition for Autonomous Underwater Vehicles written by Mark A. Compton and published by . This book was released on 1992 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Reactive Obstacle Avoidance for the REMUS Autonomous Underwater Vehicle Utilizing a Forward Looking Sonar written by and published by . This book was released on 2006 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: One day fully autonomous AUV's will no longer require human interactions to complete its missions. To make this a reality, the AUV must be able to safely navigate in unfamiliar environments with unknown obstacles. This thesis builds on previous work conducted at NPS's Center for AUV Research to improve the autonomy of the REMUS class of AUVs with an implemented FLS. The first part of this thesis deals with accurate path following with the use of look-ahead pitch calculations. With the use of a SIMULINK model, constraints surrounding obstacle avoidance path planning are then explored, focusing on optimal sensor orientation issues. Two path planning methods are developed to address the issues of a limited sonar field of view and uncertainties brought on by an occlusion area. The first approach utilizes a pop-up maneuver to increase the field of view and minimize the occlusion area, while the second approach creates a path with the addition of a spline. Comparing the two methods, it was concluded that spline addition planner provided a robust optimal obstacle avoidance path and along with the look-ahead pitch controller completes the design of a back-seat driver to improve REMUS s survivability in an unknown environment. REMUS, AUV, UUV, Autonomous Underwater Vehicle, Reactive Obstacle Avoidance, Forward Looking Sonar, Vertical Plane, Pitch Controller, Spline, Gaussian, Occlusion, Optimal Sensor Orientation.

Download or read book Obstacle Avoidance Control for the REMUS Autonomous Underwater Vehicle written by Christopher D. Chuhran and published by . This book was released on 2003-09 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the Navy continues its development of unmanned underwater vehicles, the need for total autonomous missions grows. Autonomous Underwater Vehicles (AUV) allow for advances in mine warfare, harbor reconnaissance, undersea warfare and more. Information can be collected from AUVs and downloaded into a ship or battle group's network. As AUVs are developed it is clear forward-look sonar will be required to be able to detect obstacles in front of its search path. Common obstacles in the littoral environment include reefs and seawalls which an AUV will need to rise above to pass. This thesis examines the behavior and control system required for an AUV to maneuver over an obstacle in the vertical plane. Hydrodynamic modeling of a REMUS vehicle enables a series of equations of motion to be developed to be used in conjunction with a sliding mode controller to control the elevation of the AUV. A two-dimensional, 24 deg. vertical scan forward look sonar with a range of 100 m is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for use in MATLAB simulations. The sonar 'image' of the vertical obstacle allows for an increasing altitude command that forces the AUV to pass safely over the obstacles at a reasonable rate of ascent and pitch angle. Once the AUV has passed over the obstacle, the vehicle returns to its regular search altitude. This controller is simulated over different types of obstacles.

Download or read book Experiments with the REMUS AUV written by Matthew D. Phaneuf and published by . This book was released on 2004-06-01 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis centers on actual field operations and post-mission analysis of data acguired using a REMUS AUV operated by tbe Naval Postgraduate School center for Autonomous Underwater Vehicle Research. It was one of many platforms tbat were utilized for data collection during AOSN II, (Autonomous Oceanograpbic Sampling Network II), an ONR sponsored exercise for dynamic oceanograpnic data taking and model based analysis using adaptive sampling. Tbe vebicle's ability to collect oceanograpnic data consisting of conductivity, temperature, and salinity during tbis experiment is assessed and problem areas investigated. Of particular interest are the temperature and salinity profiles measured from long transect runs of 18 Km. length into tbe soutbern parts of Monterey Bay. Experimentation witn tne REMUS as a mine detection asset was also performed. Tbe design and development of the mine hunting experiment is discussed as well as its results and tneir analysis. Of particular interest in tbis portion of tne work is tne issue relating to repeatability and precision of contact localization, obtained from vehicle position and sidescan sonar measurements.

Download or read book Obstacle Avoidance Control for the REMUS Autonomous Underwater Vehicle written by Lynn R. Fodrea and published by . This book was released on 2002-12 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future Naval operations necessitate the incorporation of autonomous underwater vehicles into a collaborative network. In future complex missions, a forward look capability will be required to map and avoid obstacles such as sunken ships. This thesis examines obstacle avoidance behaviors using a forward- looking sonar for the autonomous underwater vehicle REMUS. Hydrodynamic coefficients are used to develop steering equations that model REMUS through a track of specified points similar to a real-world mission track. Control of REMUS is accomplished using line of sight and state feedback controllers. A two- dimensional forward-looking sonar model with a 1200 horizontal scan and a 110 meter radial range is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for implementation in MATLAE simulations. The product of bearing and range weighting functions form the gain factor for a dynamic obstacle avoidance behavior. The overall vehicle heading error incorporates this obstacle avoidance term to develop a path around detected objects. REMUS is a highly responsive vehicle in the model and is capable of avoiding multiple objects in proximity along its track path.

Download or read book Obstacle Avoidance Control for the REMUS Autonomous Underwater Vehicle written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future Naval operations necessitate the incorporation of autonomous underwater vehicles into a collaborative network. In future complex missions, a forward look capability will be required to map and avoid obstacles such as sunken ships. This thesis examines obstacle avoidance behaviors using a forward-looking sonar for the autonomous underwater vehicle REMUS. Hydrodynamic coefficients are used to develop steering equations that model REMUS through a track of specified points similar to a real-world mission track. Control of REMUS is accomplished using line of sight and state feedback controllers. A two-dimensional forward-looking sonar model with a 1200 horizontal scan and a 110 meter radial range is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for implementation in MATLAE simulations. The product of bearing and range weighting functions form the gain factor for a dynamic obstacle avoidance behavior. The overall vehicle heading error incorporates this obstacle avoidance term to develop a path around detected objects. REMUS is a highly responsive vehicle in the model and is capable of avoiding multiple objects in proximity along its track path.

Download or read book Obstacle Avoidance While Bottom Following for the REMUS Autonomous Underwater Vehicle written by and published by . This book was released on 2004 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future Naval operations necessitate the incorporation of autonomous underwater vehicles into a collaborative network. In future complex missions, a forward look capability will also be required to map and avoid obstacles such as sunken ships and reefs. Following previous work on steering control, this work examines collision avoidance behaviors in bottom following using a hypothetical forward-looking sonar for the autonomous underwater vehicle REMUS. Hydrodynamic coefficients are used to develop diving equations that model REMUS behaviors. A two-dimensional forward-looking sonar model with a 20 vertical scan and a 40 meter radial range is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for implementation in MATLAB simulations. REMUS is a highly responsive vehicle and care has taken to balance pitch and heave response to keep the obstacle to be avoided in sight during the response behavior.

Download or read book Navigation and Target Localization Performance of the AUV Remote Environmental Measuring UnitS written by Christopher John Cassidy and published by . This book was released on 2000 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Discrete Event Simulation to Assess Obstacle Location Accuracy in the REMUS Unmanned Underwater Vehicle written by Timothy E. Allen and published by . This book was released on 2004-06-01 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Navy personnel use the REMUS unmanned underwater vehicle to search for submerged objects. Navigation inaccuracies lead to errors in predicting the location of objects and thus result in increased search times for Explosive Ordnance Disposal (EOD) teams searching for the object post-mission. This thesis explores contributions to navigation inaccuracy using Discrete Event Simulation (DES) to model the vehicle's navigation system and operational performance. The DES produced for this thesis uses the JAVA-based Simkit package to simulate the navigation system in REMUS. The model considers factors affecting accuracy, such as compass error, the effect of current, transducer drop error, transducer positioning effects, and ping interval. Mines can be placed at specific locations or generated randomly. Three types of vehicles are considered in this thesis. First, a simple vehicle that navigates by Dead Reckoning is analyzed. Second, a more complex vehicle that navigates using Long-Baseline (LBL) is analyzed. Third, the vehicle is simulated to move through an area of interest in a sweeping pattern that is populated by 10 mines, each of which is randomly positioned. Data from the last vehicle are used to build three analytic models that the operator can use to improve performance. First, the probability of detection is modeled by a logit regression. Second, given that detection has occurred, the mean location offset is modeled by a linear regression. Third, the distribution of errors is shown to follow an exponential distribution. These three models enable operators to explore the impact of various inputs prior to programming the vehicle, thus allowing them to choose the best combination of vehicle parameters that minimize the offset error between the reported and actual locations. (18 tables, 33 figures, 17 refs.)

Download or read book Obstacle Avoidance Control for the REMUS Autonomous Underwater Vehicle written by Lynn Fodrea and published by . This book was released on 2002 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future Naval operations necessitate the incorporation of autonomous underwater vehicles into a collaborative network. In future complex missions, a forward look capability will be required to map and avoid obstacles such as sunken ships. This thesis examines obstacle avoidance behaviors using a forward-looking sonar for the autonomous underwater vehicle REMUS. Hydrodynamic coefficients are used to develop steering equations that model REMUS through a track of specified points similar to a real-world mission track. Control of REMUS is accomplished using line of sight and state feedback controllers. A two-dimensional forward-looking sonar model with a 1200 horizontal scan and a 110 meter radial range is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for implementation in MATLAE simulations. The product of bearing and range weighting functions form the gain factor for a dynamic obstacle avoidance behavior. The overall vehicle heading error incorporates this obstacle avoidance term to develop a path around detected objects. REMUS is a highly responsive vehicle in the model and is capable of avoiding multiple objects in proximity along its track path.

Download or read book Towards Combined Task and Motion Planning for Autonomous Underwater Vehicles written by James William McMahon and published by . This book was released on 2016 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: In oceanic research and development, autonomous underwater vehicles (AUVs) provide scientists with the ability to augment expensive manned operations at a lower cost while simultaneously exploring regions that were previously inaccessible to scientists. While the cost of these AUVs is often nontrivial, the ability to autonomously sample data from varying regions over extended time periods removes the necessity of human operations which require much higher overhead costs. Scientists are now leveraging the unique abilities of AUVs to explore new environments, scientists are now starting to use AUVs to perform sophisticated missions in deep ocean environments, under the polar ice caps, or throughout dangerous minefields in the littoral. The success of these missions, however, depends on the ability of the AUV to autonomously perform complex tasks. Toward this goal, this dissertation seeks to enhance the capabilities of AUVs so that they are able to autonomously plan the high-level actions and the low-level motions needed to accomplish complex missions. A framework is developed which makes it possible to specify such missions in a structured language resembling English, and it automatically plans the actions and motions that the AUV needs to execute in order to accomplish the mission. The mission-specification language is grounded in well-established logical formalisms such as Regular Languages and Linear Temporal Logic. The inherent structure of the mission-specification language makes it possible to construct sophisticated mission such as exploring unknown areas, searching for objects of interest, or collecting data. In doing so, the framework alleviates the burden imposed on human operators who currently need to manually input highly detailed mission specifications into multiple configuration files, which increases the risk for mission failure due to human error. Instead, the framework makes it possible for the human operators to specify the missions in an easy-to-use, structured language. The technical contribution of the dissertation stems from a novel treatment of the combined mission and motion-planning problem as a hybrid search over discrete and continuous layers. Leveraging advances in AI and Robotics, a hybrid-planning framework is developed which combines high-level AI mission planning with low-level sampling-based motion planning. High-level planning, which operates over a discrete and abstract layer, breaks down the overall mission into a sequence of tasks. Sampling-based motion planning conducts a search over the feasible motions of the AUV in order to compute a trajectory that enables the AUV to accomplish each task. When sampling-based motion planning fails to make progress it requests another high-level plan from the AI planning layer. This interplay between high-level discrete planning and sampling-based motion planning is crucial to the success of the framework. The hybrid framework can be used with any AUV. Extensive experiments have been conducted with high-fidelity simulators and real AUVs, such as OceanServer Iver2 AUV and Reliant Bluefin-21 AUV. The experimental results show the ability of the approach to effectively plan collision-free and dynamically-feasible trajectories that enable the AUV to carry out sophisticated missions, such as inspection of numerous areas, data collection, and reacquisition and identification in Mine Countermeasures. The success of the hybrid framework highlight the potential of the approach to enhance the autonomy of AUVs, making it possible to carry out sophisticated missions at a lower operational cost.

Download or read book Chemical Plume Mapping with the Remus Autonomous Underwater Vehicle written by and published by . This book was released on 2001 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: A REMUS (Remote Environmental Measuring UnitS) unmanned undersea vehicle (UUV) is being used for chemical plume mapping as part of the Office of Naval Research (ONR) Chemical Sensing in the Marine Environment (CSME) program. Bathymetric, current, temperature and fluorometric data are collected while the vehicle performs a ladder type search across and downstream of a dye source. These data are used to validate and refine an analytical plume model. Operational experiences and data collected will be presented from operations at San Clemente Island,

Download or read book Initial Development and Testing of an Adaptive Mission Planner for a Small Unmanned Underwater Vehicle written by and published by . This book was released on 2003 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Adaptive Mission Planner (AMP) was developed for the REMUS Unmanned Underwater Vehicle (UUV) in order to have the vehicle react to real-time sensor data and alter course for the purpose of chemical plume tracing. In order for a UUV to track a plume autonomously, it must implement search strategies in an intelligent manner as dictated by environmental circumstances without human intervention. Throughout the mission, the UUV will combine the sensed flow and concentration information to construct a map of likely source or plume locations. This AMP has been designed and tested in simulation at the University of California, Riverside, and has now been installed on the SPAWARSYSCEN-SD REMUS UUV. This paper will describe the search strategies and initial field tests which use the AMP to break away from the vehicle's pre-programmed missions. Two sets of experiments are described herein. The first uses bathymetry as the environmental driving input. The second uses chemical concentration as the primary input.

Download or read book Autonomous Underwater Vehicles written by Jing Yan and published by Springer. This book was released on 2022-11-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous underwater vehicles (AUVs) are emerging as a promising solution to help us explore and understand the ocean. The global market for AUVs is predicted to grow from 638 million dollars in 2020 to 1,638 million dollars by 2025 – a compound annual growth rate of 20.8 percent. To make AUVs suitable for a wider range of application-specific missions, it is necessary to deploy multiple AUVs to cooperatively perform the localization, tracking and formation tasks. However, weak underwater acoustic communication and the model uncertainty of AUVs make achieving this challenging. This book presents cutting-edge results regarding localization, tracking and formation for AUVs, highlighting the latest research on commonly encountered AUV systems. It also showcases several joint localization and tracking solutions for AUVs. Lastly, it discusses future research directions and provides guidance on the design of future localization, tracking and formation schemes for AUVs. Representing a substantial contribution to nonlinear system theory, robotic control theory, and underwater acoustic communication system, this book will appeal to university researchers, scientists, engineers, and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of AUVs. Moreover, the practical localization, tracking and formation schemes presented provide guidance on exploring the ocean. The book is intended for those with an understanding of nonlinear system theory, robotic control theory, and underwater acoustic communication systems.

Download or read book Sequential Long Baseline Navigation for REMUS An Autonomous Underwater Vehicle written by and published by . This book was released on 2001 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many of the problems of operating an AUV (autonomous underwater vehicle) can be reduced to one of navigation: How accurately do you know where you are? Navigational precision determines the ability to follow truck lines, the ability to map a target to world coordinates, and ultimately, even determines the areas where you ore willing to operate the vehicle. This paper presents the technique used for long baseline acoustic navigation by REMUS (Remote Environmental Measuring Units), a low cost AUV developed by the Oceanographic Systems Laboratory (OSL) of the Woods Hole Oceanographic Institution. Adopting the traditional long base line approach to this vehicle presents a complex problem because it must be low power, low cost and small in size, and in addition must work in a shallow water environment. The REMUS system uses a single data acquisition system and DSP to interrogate and receive multiple transponders in a sequential manner. It uses spread spectrum technology which reduces the impact of multi-path in the shallow water environment. A moored pair of acoustic transponders whose coordinates are determined using differential or P-code GPS allow the vehicle to navigate in world coordinates. The DSP minimizes the hardware requirements, thus lowering the associated hardware cost, size, and complexity. This paper describes the techniques used and provides results of this system using frequencies in the 20-30 khz band, giving a range of up to 1500 meters in water 4 meters deep, and also 10-15 khz band, giving a range of up to 7000 meters in waters 14 meters deep.

Download or read book Precision Control and Maneuvering of the Phoenix Autonomous Underwater Vehicle for Entering a Recovery Tube written by Duane T. Davis and published by . This book was released on 1996-09-01 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of range limitations imposed by speed and power supplies, covert launch and recovery of Autonomous Underwater Vehicles (AUVs) near the operating area will be required for their use in many military applications. This thesis documents the implementation of precision control and planning facilities on the Phoenix AUV that will be required to support recovery in a small tube and provides a preliminary study of issues involved with AUV recovery by submarines. Implementation involves the development of low-level behaviors for sonar and vehicle control, mid-level tactics for recovery planning, and a mission planning system for translating high-level goals into an executable mission. Sonar behaviors consist of modes for locating and tracking objects, while vehicle control behaviors provide the ability to drive to and maintain a position relative to a tracked object. Finally, a mission-planning system allowing graphical specification of mission objectives and recovery parameters is implemented. Results of underwater virtual world and in-water testing show that precise AUV control based on sonar data and its use by higher-level tactics to plan and control recovery. Additionally, the mission-planning expert system has been shown to reduce mission planning time by approximately two thirds and results in missions with fewer logical and programming errors than manually generated missions.