ECE PhD Dissertation Defense: Vikrant Shah

PhD Dissertation Defense: Visual Navigation Applications in Low Contrast Environments: Multi Sensor Iceberg Mapping

Vikrant Shah

Location: Zoom Link

Abstract: Most approaches to visual navigation make multiple assumptions about the scenes being imaged. There are implicit assumptions about the scene being predominantly static and the availability of well illuminated, texture rich, objects in the scene. In some cases these assumptions severely limit or eliminate the full applicability of visual Simultaneous Localization and Mapping (SLAM) and Structure from Motion (SfM) methodologies. This dissertation attempts to address problems where the assumptions of static scenes and texture rich objects are not valid. Motivated by the application of mapping rotating and translating icebergs, we propose a system level solution for addressing the problem of mapping large, low contrast, moving targets with slow but complicated dynamics.

Our approach leverages the complementary nature of multiple sensing modalities and utilizes a rigidly coupled combination of a subsurface multibeam sonar (a line scan sensor) and an optical camera (an area scan sensor). This allows the system to exploit the optical camera information to perform iceberg relative navigation, which can be directly used by the multibeam sonar to map the iceberg underwater. To compensate for the effect of low contrast we conducted an in-depth analysis of features detectors and descriptors on end-to-end SfM algorithms to demonstrate and understand how methodologies such as Contrast Limited Adaptive Histogram Equalization (CLAHE) and Zernike Moment descriptors help improve the overall accuracy in these challenging applications.

We merge these approaches into an algorithmic framework that allows us to compute the scale of the navigation solution and iceberg centric navigation corrections. These corrections can then be used for accurate iceberg reconstructions. This enables a quantitative analysis of our iceberg mapping efforts including volume estimation and change detection.

We successfully demonstrate our approach on real field data from three of the icebergs surveyed multiple times during the 2018 and 2019 campaigns to the Sermilik fjord in Eastern Greenland. Availability of iceberg mounted Global Navigation Satellite System (GNSS) observations during these research expeditions also allowed for a comparison of this approach against ground truth, providing additional confidence in the systems level mapping efforts. The accuracy of the reconstructions is demonstrated by estimating iceberg volumes, calculating their ablation rates, and performing change detection at a granular scale.