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	<title>unknown clustered target tracking &#8211; BIOENGINEER.ORG</title>
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		<title>Distributed Robots Excel at Tracking Unknown Clusters</title>
		<link>https://bioengineer.org/distributed-robots-excel-at-tracking-unknown-clusters/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 23 Jan 2026 05:30:47 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Adaptive robotic systems]]></category>
		<category><![CDATA[adaptive robotics algorithms]]></category>
		<category><![CDATA[collaborative robot teams]]></category>
		<category><![CDATA[Decentralized tracking]]></category>
		<category><![CDATA[decentralized tracking systems]]></category>
		<category><![CDATA[distributed robotics]]></category>
		<category><![CDATA[Mobile robot coordination]]></category>
		<category><![CDATA[unknown clustered target tracking]]></category>
		<category><![CDATA[Unknown target tracking]]></category>
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					<description><![CDATA[In an era marked by rapid advancements in robotics and artificial intelligence, the focus on innovative solutions for complex tracking tasks has escalated significantly. A recent study conducted by Chen, Dames, and Park has introduced novel paradigms in the domain of mobile robotics, specifically targeting the efficient tracking of unknown clustered targets using a decentralized [&#8230;]]]></description>
		
		
		
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