The goal of this work is to determine methods for detecting trails using statistics of LiDAR point cloud data, while avoiding reliance on a Digital Elevation Model (DEM). Creation of a DEM is a subjective process that requires assumptions be made about the density of the data points, the curvature of the ground, and other factors which can lead to very different results in the final DEM product...

Recently, the availability of low cost depth cameras has provided 3D sensing capabilities for mobile robots in the form of dense 3D point clouds, usable for applications like 3D mapping and reconstruction, shape analysis, pose tracking and object recognition. For all the aforementioned applications, processing the raw 3D point cloud in real time and at full frame rates may be infeasible due to ...

Often noisy point clouds are given as an approximation of a particular compact set of interest. A finite point cloud is a compact set. This paper proves a reconstruction theorem which gives a sufficient condition, as a bound on the Hausdorff distance between two compact sets, for when certain offsets of these two sets are homotopic in terms of the absence of μ-critical points in an annular regi...

The objective of this study is to verify the importance of the capabilities of cloud computing services in managing and analyzing big data in business organizations because the rapid development in the use of information technology in general and network technology in particular, has led to the trend of many organizations to make their applications available for use via electronic platforms hos...

With advances in technology and lowered price the use of RGB-D cameras for robot applications has become popular. They are able to provide rich information about the environment but due to the huge amount of data that they produce and often limited computational resources, processing and analysing the data is challenging. This creates the need for good and efficient compression methods. In this...