2,594 research outputs found

    Cooperative localization of marine vehicles using nonlinear state estimation

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    Underwater vehicle localization using range measurements

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 79-83).This thesis investigates the problem of cooperative navigation of autonomous marine vehicles using range-only acoustic measurements. We consider the use of a single maneuvering autonomous surface vehicle (ASV) to aid the navigation of one or more submerged autonomous underwater vehicles (AUVs), using acoustic range measurements combined with position measurements for the ASV when data packets are transmitted. The AUV combines the data from the surface vehicle with its proprioceptive sensor measurements to compute its trajectory. We present an experimental demonstration of this approach, using an extended Kalman filter (EKF) for state estimation. We analyze the observability properties of the cooperative ASV/AUV localization problem and present experimental results comparing several different state estimators. Using the weak observability theorem for nonlinear systems, we demonstrate that this cooperative localization problem is best attacked using nonlinear least squares (NLS) optimization. We investigate the convergence of NLS applied to the cooperative ASV/AUV localization problem. Though we show that the localization problem is non-convex, we propose an algorithm that under certain assumptions (the accumulative dead reckoning variance is much bigger than the variance of the range measurements, and that range measurement errors are bounded) achieves convergence by choosing initial conditions that lie in convex areas. We present experimental results for this approach and compare it to alternative state estimators, demonstrating superior performance.by Georgios Papadopoulos.S.M

    Optimal path shape for range-only underwater target localization using a Wave Glider

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    Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.Peer ReviewedPostprint (author's final draft

    Dynamic Control of Mobile Multirobot Systems: The Cluster Space Formulation

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    The formation control technique called cluster space control promotes simplified specification and monitoring of the motion of mobile multirobot systems of limited size. Previous paper has established the conceptual foundation of this approach and has experimentally verified and validated its use for various systems implementing kinematic controllers. In this paper, we briefly review the definition of the cluster space framework and introduce a new cluster space dynamic model. This model represents the dynamics of the formation as a whole as a function of the dynamics of the member robots. Given this model, generalized cluster space forces can be applied to the formation, and a Jacobian transpose controller can be implemented to transform cluster space compensation forces into robot-level forces to be applied to the robots in the formation. Then, a nonlinear model-based partition controller is proposed. This controller cancels out the formation dynamics and effectively decouples the cluster space variables. Computer simulations and experimental results using three autonomous surface vessels and four land rovers show the effectiveness of the approach. Finally, sensitivity to errors in the estimation of cluster model parameters is analyzed.Fil: Mas, Ignacio Agustin. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kitts, Christopher. Santa Clara University; Estados Unido
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