High-resolution Underwater Robotic Vision-based Mapping and 3D Reconstruction for Archaeology - Robotics Institute Carnegie Mellon University

High-resolution Underwater Robotic Vision-based Mapping and 3D Reconstruction for Archaeology

Matthew Johnson-Roberson, Mitch Bryson, Ariell Friedman, Oscar Pizarro, Giancarlo Troni, Paul Ozog, and Jon C. Henderson
Journal Article, Journal of Field Robotics, Vol. 34, No. 4, pp. 625 - 643, June, 2017

Abstract

Documenting underwater archaeological sites is an extremely challenging problem. Sites covering large areas are particularly daunting for traditional techniques. In this paper, we present a novel approach to this problem using both an autonomous underwater vehicle (AUV) and a diver-controlled stereo imaging platform to document the submerged Bronze Age city at Pavlopetri, Greece. The result is a three-dimensional (3D) reconstruction covering 26,600 m2 at a resolution of 2 mm/pixel, the largest-scale underwater optical 3D map, at such a resolution, in the world to date. We discuss the advances necessary to achieve this result, including i) an approach to color correct large numbers of images at varying altitudes and over varying bottom types; ii) a large-scale bundle adjustment framework that is capable of handling upward of 400,000 stereo images; and iii) a novel approach to the registration and rapid documentation of an underwater excavations area that can quickly produce maps of site change. We present visual and quantitative comparisons to the authors' previous underwater mapping approaches.

BibTeX

@article{Johnson-Roberson-2017-130180,
author = {Matthew Johnson-Roberson and Mitch Bryson and Ariell Friedman and Oscar Pizarro and Giancarlo Troni and Paul Ozog and Jon C. Henderson},
title = {High-resolution Underwater Robotic Vision-based Mapping and 3D Reconstruction for Archaeology},
journal = {Journal of Field Robotics},
year = {2017},
month = {June},
volume = {34},
number = {4},
pages = {625 - 643},
}