Technology and Field Demonstration of Robotic Search for Antarctic Meteorites - Robotics Institute Carnegie Mellon University

Technology and Field Demonstration of Robotic Search for Antarctic Meteorites

Journal Article, International Journal of Robotics Research, Vol. 19, No. 11, pp. 1015 - 1032, November, 2000

Abstract

Meteorites are the only significant source of material from other planets and asteroids, and therefore are of immense scientific value. Antarctica? frozen and pristine environment has proven to be the best place on Earth to harvest meteorite specimens. The lack of melting and surface erosion keep meteorite falls visible on the ice surface in pristine condition for thousands of years. In this article we describe the robotic technologies and field demonstration that enabled the first discovery of Antarctic meteorites by a robot. Using a novel autonomous control architecture, specialized science sensing, combined manipulation and visual servoing, and Bayesian classification, the Nomad robot found and classified five indigenous meteorites during an expedition to the remote site of Elephant Moraine in January 2000. This article first overviews Nomad? mechatronic systems, and details the control architecture that governs the robot? autonomy and classifier that enables the autonomous interpretation of scientific data. It then focuses on the technical results achieved during field demonstrations at Elephant Moraine. Finally, the article discusses the benefits and limitations of robotic autonomy in science missions. Science autonomy is shown as a capable and expandable architecture for exploration and in situ classification. Inefficiencies in the existing implementation are explained with a focus on important lessons that outline future work.

BibTeX

@article{Apostolopoulos-2000-8153,
author = {Dimitrios (Dimi) Apostolopoulos and Michael D. Wagner and Benjamin Shamah and Liam Pedersen and Kimberly Shillcutt and William (Red) L. Whittaker},
title = {Technology and Field Demonstration of Robotic Search for Antarctic Meteorites},
journal = {International Journal of Robotics Research},
year = {2000},
month = {November},
volume = {19},
number = {11},
pages = {1015 - 1032},
keywords = {robotic meteorite search, science autonomy, Bayesian meteorite classifier},
}