RSSI Map-Based Trajectory Design for UGV Against Malicious Radio Source: A Reinforcement Learning Approach-Reference-Cited by-同舟云学术

RSSI Map-Based Trajectory Design for UGV Against Malicious Radio Source: A Reinforcement Learning Approach

Published:2023-04 Issue:4 Volume:24 Page:4641-4650
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Han Zhaoyang¹,Yang Yaoqi²^ORCID,Wang Weizheng³^ORCID,Zhou Lu⁴^ORCID,Gadekallu Thippa Reddy⁵^ORCID,Alazab Mamoun⁶^ORCID,Gope Prosanta⁷^ORCID,Su Chunhua¹^ORCID

Affiliation:

1. Division of Computer Science, The University of Aizu, Aizuwakamatsu, Fukushima, Japan

2. Graduate School, Army Engineering University of PLA, Nanjing, China

3. Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong

4. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

5. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India

6. College of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT, Australia

7. Department of Computer Science, The University of Sheffield, Sheffield, U.K

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10086684/09990571.pdf?arnumber=9990571

Reference32 articles.

1. RSSI Measurements for RFID Tag Classification in Smart Storage Systems

2. Cooperative Persistent Surveillance on a Road Network by Multi-UGVs with Detection Ability

3. Indoor Radio Map Construction and Localization With Deep Gaussian Processes

4. A Survey on Indoor Vehicle Localization Through RFID Technology

5. Scattered data interpolation methods for electronic imaging systems: a survey

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