Juan Castorena

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One of the major problems associated with LIDAR sensing is that significant amounts of data must be collected to obtain detailed topographical information about a region. Current efforts to solve this problem have focused on designing compression algorithms which operate on the collected data. Typical compression algorithms, however, require the collection(More)
The 3D imaging community has begun a transition to full-waveform (FW) LIDAR systems which image a scene by emitting laser pulses in a particular direction and capturing the entire temporal envelope of each echo. By scanning a region, connected 1D profile waveforms of the 3D scenes can be readily obtained. In general, FW systems capture more detailed(More)
We present a new method for joint automatic extrinsic calibration and sensor fusion for a multimodal sensor system comprising a LIDAR and an optical camera. Our approach exploits the natural alignment of depth and intensity edges when the calibration parameters are correct. Thus, in contrast to a number of existing approaches, we do not require the presence(More)
In this paper, we address the problem of sampling the LIDAR range map. The significance of this problem is based upon the fact that large datasets generated by sampling inefficiently impose storage, processing and transmission limitations. Current compression approaches addressing these issues rely on collecting large amounts of data to analyze and throw(More)
In this paper, we investigate the problem of determining the conditions under which the restricted isometry property (RIP) is satisfied for a particular type of matrix referred to in here as a banded random matrix (BRM). Such matrices have been recognized as suitable models for a number of compressive-sensing based sampling architectures, including the(More)
In this work, we propose an alternative formulation to the problem of ground reflectivity grid-based localization involving laser-scanned data from multiple LIDARs mounted on autonomous vehicles. The driving idea of our localization formulation is an alternative edge reflectivity grid representation, which is invariant to laser source, angle of incidence,(More)
Third generation LIDAR full-waveform (FW) based systems collect 1D temporal profiles of laser pulses reflected by the intercepted objects to construct depth profiles along each pulse path. By emitting a series of pulses towards a scene using a predefined scanning pattern, a 3D image containing spatial-depth information can be constructed. Achieving(More)