Efficient sensory perception and processing are crucial to mobile robot navigation. As sensor technology advances, conventional processing methods bottleneck, crippling real time operation. Researchers have recently developed a low-cost LIDAR system capable of generating 10,000 samples per second, challenging sensor data processing rates. This project is efficiently and robustly compressing sensory range-bearing data by applying the log-Hough transform to recognize walls and characterize them parametrically.Walls are the dominant navigation reference features in built environments. The log-Hough transform converts a long chain of sensor hits on a wall to a single data point representing line parameters. This succinct data can be used for localization against a priori maps without overloading communications channels to the navigator. LIDAR data is being gathered and analyzed with respect to range and bearing resolution; software implements the log-Hough transform on this data.Commercial Applications:Research will result in a Commercial product for mobile robots, delivery systems, floor cleaners, sentries, and mobile vehicles.
