[1] The Rock Abrasion Tool (RAT) on board the Mars Exploration Rovers (MER) is a grinding tool designed to remove dust coatings and/or weathering rinds from rocks and expose fresh rock material. Four magnets of different strengths that are built into the structure of the RAT have been attracting substantial amounts of magnetic material during RAT activities from rocks throughout both rover missions. The RAT magnet experiment as performed on Spirit demonstrates the presence of a strongly ferrimagnetic phase in Gusev crater rocks, which based on Mössbauer and visible/near-infrared reflectance spectra is interpreted as magnetite. The amount of abraded rock material adhering to the magnets varied strongly during the mission and is correlated in a consistent way to the amount of magnetite inferred from Mössbauer spectra for the corresponding rock. The RAT magnet experiment as performed on Opportunity also indicates the presence of a strongly ferrimagnetic phase in outcrops, such as magnetite or an altered version of magnetite. However, the evidence is weaker than in the case of Spirit. According to data from the a particle X-ray spectrometer (APXS) and the Mössbauer spectrometer (MB), the Eagle crater outcrops should not contain magnetite and their magnetization should not exceed 0.03 A m 2 kg À1 . However, this assertion seems to be in contradiction with the results of the RAT magnet experiment. The evidence for a strongly ferrimagnetic phase at low abundance in the Meridiani outcrops is discussed.
This paper compares some of the common tools and techniques that enable state-of-the-art systems to provide high-level control of mobile sensor networks. There is currently a great deal of interest in employing unmanned and autonomous vehicles in intelligence, surveillance, and reconnaissance operations. Although this paper addresses issues common to all mobile sensor networks, the applications presented are typically associated with autonomous vehicles. We focus speciflcally on three high-level areas: I. mission deflnition languages that allow human users to compose missions deflned in terms of tasks, 2. communicationaddressing degradation and loss and relationship to underlying system architecture design, and 3. task allocation among the assets.
This paper describes a modular system architecture for mobile robotics. It presents the view of an individual robot as a collection of many small pieces of hardware and software grouped into functional subsystems. A set of robots can then join together to form a larger system. The goal of this work is to describe a software design philosophy and architecture that is flexible yet robust enough to meet the challenges of the mobile robotics domain. The guiding design principle is bottom-to-top modularization, from individual algorithms, to software executables, to functional groupings of executables. These functional groupings are presented as canonical subsystems for collaborative robotics, applicable to a wide range of robotics systems. A multi-agent multi-user UAV application is presented as a case study and proof of the generality of the design philosophy.
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