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Probabilistic methods provide a powerful paradigm for modeling of robot motion and its environment; a precursor for autonomous navigation of mobile robots. As a graduate‐level engineering course, probabilistic robotics encompasses the techniques used in robot localization and mapping in unstructured environments. This article presents a simulation and animation software program developed mainly as...
This paper presents a sensor fusion framework that incorporates a monocular vision system, laser range finder and an inertial navigation sensor (INS) for localization of mobile robots and manipulators. The proposed method is particularly useful for applications in which there is a featured wall or floor in proximity to the robots. Examples include unmanned ground vehicles (UGV), unmanned aerial vehicles...
This paper describes a visual simultaneous localization and mapping (VSLAM) method for a pipe inspection robot that can serve as a carrier for nondestructive testing (NDT) sensors inside in-service water mains. The proposed method features a multi-sensor fusion system that simultaneously executes two important functions of the robot: construct a global image of the internal surface of the pipe and...
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