FRC Seminar:
Camera and LIDAR Fusion for Mapping in Dark Environments
Uland Wong
PhD Student, Robotics Institute, Carnegie Mellon University
Thursday, April 30th, 2009
Abstract: Unlit diffuse environments like subterranean voids on earth and planetary surfaces elsewhere are of great interest for robotic exploration and exploitation. These environments pose unique obstacles and constraints, including the necessity for active perception and illumination. However, uniformity of albedo, lack of external lighting and known surface reflectance provide additional assumptions which can be used to enhance 3D-mapping and photographic data collected from robots. This talk presents a method for improving the accuracy of super-resolution point clouds by fusing actively illuminated HDR camera imagery with LIDAR data in dark Lambertian environments. The key approach is shape recovery from estimation of the illumination function and integration in a Markov Random Field (MRF) framework. Experimental results collected from a virtual reconstruction of the Bruceton Research Mine in Pittsburgh, PA are also presented.
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