RAPID: Reinforcement Learning-Aided Femtocell Placement for Indoor Drone Localization
Author:
Affiliation:
1. WayWave Inc,Virginia,USA
2. George Washington University,Department of Computer Science,Washington,D.C.,USA
3. Virginia Tech,Department of Electrical & Computer Engineering,Virginia,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10637481/10637507/10637529.pdf?arnumber=10637529
Reference24 articles.
1. Optimal scheduling and quantitative analysis for multi-flying warehouse scheduling problem: Amazon airborne fulfillment center;Jeong,2022
2. Indoor Drone Positioning: Accuracy and Cost Trade-Off for Sensor Fusion
3. Wi-drone
4. PILOT: High-Precision Indoor Localization for Autonomous Drones
5. A survey on reinforcement learning in aviation applications
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