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@@ -34,12 +34,11 @@ <h2>Robust Autonomy in Complex Environments</h2>
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robots&nbsp;achieve robust autonomy in complex physical
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environments. Specific goals include improving the reliability of
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autonomous navigation for unmanned underwater, surface, ground and aerial
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vehicles
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subjected to noise-corrupted and drifting sensors, incomplete knowledge
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vehicles subjected to noise-corrupted and drifting sensors, bandwidth-limited communications, incomplete knowledge
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of the environment, and tasks that require interaction with surrounding
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objects and structures. Our recent work uses artificial intelligence to
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improve the situational awareness of mobile robots operating in degraded conditions, </span></p>
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improve the situational awareness of mobile robots operating in degraded conditions,
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and to enable intelligent robot decision-making under uncertainty.</span></p>
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<br />
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<div style="text-align: center;"> <img style="width: 251px; height: 131px;" alt="" src="./index_files/VideoRay1.jpg" /> <img style="width: 258px; height: 131px;" alt="" src="./index_files/VideoRay2.jpg" /> <img style="width: 210px; height: 131px;" alt="" src="./jackal-kinova.png" /><br />
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</div>

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