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<p>The advancement of robot technology holds many opportunities for military applications. One area of research  being done is simultaneous localization and mapping (SLAM). SLAM uses a robot's sensors to generate a map of the  area while maintaining its current position within that map. SLAM research is built upon the assumption that all of the  sensors are working correctly. Since field conditions are likely to cause erratic sensor function due to damage or  inclement weather conditions, this assumption must be addressed.  The goal of our research is to discover methods of effectively performing self-diagnostic checks on robots to  detect failures and malfunctions in sensors. There has been little work in the area of error detection in sensors, and  what little work has been done has limited applications. This thesis will perform a series of experiments using a variety  of different error detection techniques. It is our hope that the methods developed will prove to be applicable to a  variety of real world systems.
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<br>Subjects: Computer science; Robotics; Introspection</div>
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<dl><dd>Valerius, Andrew J.</dd>
<dd>Smeltz, Jeremy M.</dd></dl></div>
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