Достижения в области робототехники и автоматизации

Algorithm on Converting a 2D Scanning LiDAR to 3D for use in Autonomous Indoor Navigation

Abstract

Matthew A Cooper, John F. Raquet and Rick Patton

Autonomous indoor navigation is synonymous with military centric autonomous navigation in GPS-denied environments. Unmanned aerial systems (UAS) are routinely connected to autonomous navigation. This combination of technology has many disparate uses such as in kids toys, photography, and military applications. For each of these areas a major concern is size, weight, and power (SWaP) in the product design. SWaP has a direct effect on the operations of an autonomous UAS such as on the flight time, the maneuverability, controllability, and the durability. This paper presents a basic algorithm describing one aspect of reducing SWaP on an autonomous quad-rotor UAS, by converting a 2D scanning LiDAR sensor to a 3D sensor, thus eliminating the need for additional sensors used to perform localization and mapping. Much that is described here is derived from the thesis work presented by Cooper. The majority of work was performed during a Master’s Thesis investigation by M. A. Cooper titled “Converting a 2D Scanning LiDAR to a 3D System for Use on Quad-Rotor UAVs in Autonomous Navigation.” The work presented here develops the generalized calibration procedure.