Mining GPS data for extracting significant places

Authors:
Gabriel Agamennoni;Juan Nieto;Eduardo Nebot
Affiliations:
Australian Center for Field Robotics, University of Sydney, Australia;Australian Center for Field Robotics, University of Sydney, Australia;Australian Center for Field Robotics, University of Sydney, Australia
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

Citing 5
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Abstract

This paper addresses the problem of safety in mining applications. It presents new metrics that can be used to determine dangerous situations during mine operation in real time. It also presents a fast and robust algorithm for extracting significant places from information logged by a state-of-the-art collision avoidance system. Determining significant places provides valuable context information in a variety of applications such as map building, vehicle tracking and user assistance. In our case, we are interested in obtaining context information as a preliminary step towards improving mining safety. The algorithm presented here is validated with experimental data obtained from a fleet of haulage vehicles operating in various open pit mines.