CMU master's thesis: Data Structure for Efficient Dynamic Processing in 3-D

J. Lalonde
master's thesis, tech. report CMU-RI-TR-06-22, Robotics Institute, Carnegie Mellon University, May, 2006.

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abstract

In this paper, we consider the problem of the dynamic processing of large amounts of sparse three-dimensional data. It is assumed that computations are performed in a neighborhood defined around each point in order to retrieve local properties. This general kind of processing can be applied to a wide variety of applications. We propose a new, efficient data structure and corresponding algorithm that significantly improve the speed of the range search operation and that are suitable for on-line operation, where data is accumulated dynamically. The method relies on taking advantage of overlapping neighborhoods and the reuse of previously computed data as the algorithm scans each data point. To demonstrate the dynamic capabilities of the data structure, we use data obtained from a laser radar mounted on a ground mobile robot operating in complex, outdoor environments. We show that this approach considerably improves the speed of an established 3-D perception processing algorithm.