Fall 2013 GRASP Seminar: Byron Stanley, Massachusetts Institute of Technology – Lincoln Labs, “Enabling Robust AGV Localization in Adverse Conditions”

Abstract: Few, if any, autonomous ground vehicles (AGVs) navigate successfully in adverse conditions, such as snow or GPS denied areas. A fundamental limitation is that they are using optical sensors, such as LIDAR or imagers, to fuse with GPS/INS solutions to localize themselves. When the optical surfaces become distorted or obscured, such as with snow, dust, or heavy rain, there is no robust way to localize the vehicle to the required accuracy. GPS/INS solutions, which are in themselves insufficient to maintain a vehicle within a lane for extended time periods, also fail around significant RF noise or jamming, tall buildings, trees, and other blocking or multipath scenarios.
This talk presents a new MIT Lincoln Laboratory developed mode of vehicle localization that has low sensitivity to the failure modes of LIDAR, camera, and GPS/INS sensors. We have demonstrated that a uniquely designed Localizing Ground Penetrating Radar (LGPR) array can map the relatively static area below the road surface and use that map as a reference, in previously mapped areas, to localize an autonomous vehicle at over 60Hz to an accuracy of approximately 2 cm rms. Implications for robust autonomous ground vehicle localization and utility to other industries will be discussed.