Title :
Mining GPS data for extracting significant places
Author :
Agamennoni, Gabriel ; Nieto, Juan ; Nebot, Eduardo
Author_Institution :
Australian Center for Field Robot., Univ. of Sydney, Sydney, NSW, Australia
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.
Keywords :
Global Positioning System; collision avoidance; data handling; geographic information systems; mining; safety; GPS data; collision avoidance system; context information; dangerous situations; haulage vehicles; mine operation; mining safety; significant places extraction; Australia; Content addressable storage; Context-aware services; Data mining; Feedback; Global Positioning System; Road accidents; Road vehicles; Safety; Vehicle driving;
Conference_Titel :
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4244-2788-8
Electronic_ISBN :
1050-4729
DOI :
10.1109/ROBOT.2009.5152475