Abstract
With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation – may it be personal robotics or spacecraft navigation.
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This work was made possible by NASA Goddard Space Flight Center through a contract with the Satellite Servicing Capabilities Office (contract NNG14CR58C, subcontract METSB0043).
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Rhodes, A.P., Christian, J.A. & Evans, T. A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation. J of Astronaut Sci 64, 414–445 (2017). https://doi.org/10.1007/s40295-016-0108-y
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DOI: https://doi.org/10.1007/s40295-016-0108-y