Simultaneous Localization and Mapping (SLAM), is a technology used in robotics and computer vision. It involves the simultaneous computation of a device’s location (localization) within an unknown environment and the creation of a map of that environment. In essence, SLAM enables a device, such as a robot or a sensor-equipped vehicle, to navigate and understand its surroundings in real-time.

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Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data

Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data We propose a new method to detect acoustic signals by matching distributed acoustic sensing data with simulation. In the simulation of the dynamic strain on an optical fiber, the optical fiber layouts and the gauge length are properly incorporated. We apply the proposed method to the acoustic-source localization and demonstrate the method localizes the source accurately even under the layouts which include the straight optical fiber for the sensing points with the large gauge-length settings.