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2 October 2006 Autonomous robot navigation using vision- and sensor-based algorithm
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ALVIN-VII is an autonomous vehicle designed to compete in the AUVSI Intelligent Ground Vehicle Competition (IGVC). The competition consists of two events, the Autonomous Challenge and Navigation Challenge. Using tri-processor control architecture the information from sonar sensors, cameras, GPS and compass is effectively integrated to map out the path of the robot. In the Autonomous Challenge, the real time data from two Firewire web cameras and an array of four sonar sensors are plotted on a custom-defined polar grid to identify the position of the robot with respect to the obstacles in its path. Depending on the position of the obstacles in the grid, a state number is determined and a command of action is retrieved from the state table. The image processing algorithm comprises a series of steps involving plane extraction, morphological analysis, edge extraction and interpolation, all of which are statistically based allowing optimum operation at varying ambient conditions. In the Navigation Challenge, data from GPS and sonar sensors are integrated on a polar grid with flexible distance thresholds and a state table approach is used to drive the vehicle to the next waypoint while avoiding obstacles. Both algorithms are developed and implemented using National Instruments (NI) hardware and LabVIEW software. The task of collecting and processing information in real time can be time consuming and hence not reactive enough for moving robots. Using three controllers, the image processing is done separately for each camera while a third controller integrates the data received through an Ethernet connection.
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Susmita Bhandari, Allison Mathis, Kashif Mohiuddin, David Pietrocola, Maria Restrepo, and David J. Ahlgren "Autonomous robot navigation using vision- and sensor-based algorithm", Proc. SPIE 6384, Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision, 63840O (2 October 2006);

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