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Existing approaches to visual Simultaneous Localization and Mapping (SLAM) typically utilize points as visual feature primitives to represent landmarks in the environment. Since these techniques mostly use image points from a standard feature point detector, they do not explicitly map objects or regions of interest. Our work is motivated by the need for different SLAM techniques in path and riverine...
We present a real-time monocular vision based range measurement method for Simultaneous Localization and Mapping (SLAM) for an Autonomous Micro Aerial Vehicle (MAV) with significantly constrained payload. Our navigation strategy assumes a GPS denied manmade environment, whose indoor architecture is represented via corner based feature points obtained through a monocular camera. We experiment on a...
We present new realtime path planning and collision avoidance algorithms for an autonomous rover equipped with a laser range finder to be used as a platform for multi-agent navigation and control in unknown environments. For successful navigation, such tasks as localization, map-building, and collision avoidance should be handled at the vehicle level. The proposed architecture covers these aspects...
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