unmanned aerial vehicle path planning algorithm based on deep reinforcement learning (IEEE Access)
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unmanned aerial vehicle path planning algorithm based on deep reinforcement learning
Unmanned Aerial Vehicle Path Planning Algorithm Based On Deep Reinforcement Learning, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/reinforcement+learning+algorithm/unmanned+aerial+vehicle+path+planning+algorithm+based+on+deep+reinforcement+learning/pm40667977-620-9-17
Average 90 stars, based on 1 article reviews
Unmanned Aerial Vehicle Path Planning Algorithm Based On Deep Reinforcement Learning, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/reinforcement+learning+algorithm/unmanned+aerial+vehicle+path+planning+algorithm+based+on+deep+reinforcement+learning/pm40667977-620-9-17
Average 90 stars, based on 1 article reviews
unmanned aerial vehicle path planning algorithm based on deep reinforcement learning - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: Low-noise trajectory optimization of urban air mobility in the urban environment using deep reinforcement learninga). Article Snippet: This study proposes a method for optimizing low-noise flight trajectory for urban air mobility (UAM) in urban environments using deep reinforcement learning (DRL).. The objective is to efficiently derive flight trajectories that minimize noise impact on ground observers as UAM vehicles approach a vertiport for landing.. Noise data were calculated for various flight velocities, and a deep learning (DL) model was employed to estimate noise map from noise propagation. |