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This paper presents a theoretical framework for identification of defects by a sensor network under uncertainties. While location of sensors are not known due to their inspection due to limited knowledge on the structure to be inspected, existing inspection methods do not take uncertainties of sensor locations into account for the localization of defects. The proposed theoretical framework formulates...
This paper presents the element-based method, which can be used for recursive Bayesian estimation (RBE) in robotic operations such as search and tracking involving moving targets. The use of shape functions to define a set of irregularly shaped elements allows the target PDF to be continuously, and thus accurately, represented over the target space. A comparison with the grid-based method first shows...
This paper presents a feedforward control strategy for a robotic manipulator based on a belief function. The belief about a target's next location, as described by a probability density function, is maintained by a recursive Bayesian process that fuses observations with a target motion model. A sensor model that incorporates positive and negative sensor readings allows the single belief function to...
This paper presents a coordinated control technique that allows heterogeneous vehicles to autonomously search for and track multiple targets using recursive Bayesian filtering. A unified sensor model and a unified objective function are proposed to enable search-and-tracking (SAT) within the recursive Bayesian filter framework. The strength of the proposed technique is that a vehicle can switch its...
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