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		<title>Simple Machine Learning Model Teaches Robots to Dodge Obstacles in Crowded Spaces</title>
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		<pubDate>Tue, 06 Oct 2026 09:15:37 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[A* algorithm]]></category>
		<category><![CDATA[autonomous mobile robot]]></category>
		<category><![CDATA[block coordinate descent]]></category>
		<category><![CDATA[collision avoidance]]></category>
		<category><![CDATA[fuzzy logic controller]]></category>
		<category><![CDATA[infrared sensors]]></category>
		<category><![CDATA[logistic regression]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[obstacle avoidance]]></category>
		<category><![CDATA[path planning]]></category>
		<category><![CDATA[ultrasonic sensor]]></category>
		<category><![CDATA[vector field histogram]]></category>
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					<description><![CDATA[Researchers have developed an adaptive logistic regression model that lets low-cost autonomous robots classify obstacles and steer through dense environments more effectively than several established path planning methods.]]></description>
		
		
		
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