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	<title>trajectory generation &#8211; BIOENGINEER.ORG</title>
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		<title>Drone Learns to Chase Moving Targets by Fusing Vision AI With Reinforcement Learning</title>
		<link>https://bioengineer.org/drone-learns-to-chase-moving-targets-by-fusing-vision-ai-with-reinforcement-learning/</link>
		
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		<pubDate>Mon, 12 Oct 2026 15:34:59 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Computer Vision]]></category>
		<category><![CDATA[control systems]]></category>
		<category><![CDATA[drone navigation]]></category>
		<category><![CDATA[dynamic target tracking]]></category>
		<category><![CDATA[image-based visual servoing]]></category>
		<category><![CDATA[LSTM]]></category>
		<category><![CDATA[obstacle avoidance]]></category>
		<category><![CDATA[Q-learning]]></category>
		<category><![CDATA[Reinforcement Learning]]></category>
		<category><![CDATA[trajectory generation]]></category>
		<category><![CDATA[unmanned aerial vehicle]]></category>
		<category><![CDATA[YOLOv8]]></category>
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					<description><![CDATA[Researchers in China have built a drone trajectory generation system that combines YOLOv8 detection, LSTM motion prediction, and Q-learning-optimized nonlinear visual servoing to keep moving targets in view, achieving a 99.02 percent obstacle avoidance rate in tests.]]></description>
		
		
		
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