The Experts below are selected from a list of 17418 Experts worldwide ranked by ideXlab platform
Olav Egeland - One of the best experts on this subject based on the ideXlab platform.
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time varying exponential stabilization of the position and attitude of an underactuated Autonomous Underwater Vehicle
IEEE Transactions on Automatic Control, 1999Co-Authors: Kristin Y Pettersen, Olav EgelandAbstract:The paper considers feedback stabilization of the position and attitude of an Autonomous Underwater Vehicle (AUV) with a reduced number of actuators. A nonlinear model describing both the dynamics and the kinematics of an AUV is studied. The paper shows that previous results on attitude stabilization of a spacecraft can be applied to exponentially stabilize both the position and attitude of an AUV using only four, possibly three, actuators. Simulation results are presented.
Kristin Y Pettersen - One of the best experts on this subject based on the ideXlab platform.
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time varying exponential stabilization of the position and attitude of an underactuated Autonomous Underwater Vehicle
IEEE Transactions on Automatic Control, 1999Co-Authors: Kristin Y Pettersen, Olav EgelandAbstract:The paper considers feedback stabilization of the position and attitude of an Autonomous Underwater Vehicle (AUV) with a reduced number of actuators. A nonlinear model describing both the dynamics and the kinematics of an AUV is studied. The paper shows that previous results on attitude stabilization of a spacecraft can be applied to exponentially stabilize both the position and attitude of an AUV using only four, possibly three, actuators. Simulation results are presented.
Brian Bingham - One of the best experts on this subject based on the ideXlab platform.
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Variable buoyancy control for a bottom skimming Autonomous Underwater Vehicle
2014 Oceans - St. John's, 2014Co-Authors: Anthony H. Sylvester, Jeffrey A. Delmerico, A Zachary Trimble, Brian BinghamAbstract:Two feedback controllers are presented that utilize data averaging and model-based estimation to offset the effects of sensor noise and achieve precise control of an Autonomous Underwater Vehicle (AUV) variable buoyancy system (VBS). Operation of the bottom skimming AUV requires a constant reaction force between the seabed and the Vehicle. While performing a mission, variable seafloor topography and a changing payload weight requires the use of a VBS to maintain the reaction force. Two traits of the VBS system that make this a challenging problem are the presence of sensor noise and fast on/off actuation relative to the sensor update rate. It was discovered that both controllers function under these conditions but the model-based controller provides more precise control of the system. This paper presents a comparison between these two control algorithms based on both simulation results and field experiments in a coastal environment.
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techniques for deep sea near bottom survey using an Autonomous Underwater Vehicle
The International Journal of Robotics Research, 2007Co-Authors: DanaR R Yoerger, Michael V Jakuba, Albert M Bradley, Brian BinghamAbstract:This paper reports the development and at-sea deployment of a set of algorithms that have enabled the Autonomous Underwater Vehicle ABE to conduct near-bottom surveys in the deep sea. Algorithms for long baseline acoustic positioning, terrain-following, and automated nested surveys are reported.
Daniela Rus - One of the best experts on this subject based on the ideXlab platform.
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data muling over Underwater wireless sensor networks using an Autonomous Underwater Vehicle
International Conference on Robotics and Automation, 2006Co-Authors: Matthew Dunbabin, Iuliu Vasilescu, Peter Corke, Daniela RusAbstract:We present algorithms, systems, and experimental results for Underwater data muling. In data muling a mobile agent interacts with static agents to upload, download, or transport data to a different physical location. We consider a system comprising an Autonomous Underwater Vehicle (AUV) and many static Underwater sensor nodes (USN) networked together optically and acoustically. The AUV can locate the static nodes using vision and hover above the static nodes for data upload. We describe the hardware and software architecture of this Underwater system, as well as experimental data
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data muling over Underwater wireless sensor networks using an Autonomous Underwater Vehicle
Faculty of Built Environment and Engineering; Institute for Future Environments, 2006Co-Authors: Matthew Dunbabin, Iuliu Vasilescu, Peter Corke, Daniela RusAbstract:We present algorithms, systems, and experimental results for Underwater data muling. In data muling a mobile agent interacts with static agents to upload, download, or transport data to a different physical location. We consider a system comprising an Autonomous Underwater Vehicle (AUV) and many static Underwater Sensor Nodes (USN) networked together optically and acoustically. The AUV can locate the static nodes using vision and hover above the static nodes for data upload. We describe the hardware and software architecture of this Underwater system, as well as experimental data. © 2006 IEEE.
Ananias Pascoal - One of the best experts on this subject based on the ideXlab platform.
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3D path following for Autonomous Underwater Vehicle
Proceedings of the IEEE Conference on Decision and Control, 2000Co-Authors: P. Encarnação, Ananias PascoalAbstract:A new methodology is proposed for the design of path following systems for Autonomous Underwater Vehicles. Global convergence to reference paths is achieved with a nonlinear control strategy that takes explicitly into account the dynamics of the Vehicle. Formal convergence proofs are indicated. Simulation results with the model of a prototype Autonomous Underwater Vehicle are presented to illustrate the performance of the path following system derived.
