Trajectory Planning for A Massive Number of UAVs in the Environment with Static and Dynamic Obstacles: A Mean Field Game Approach-Reference-Cited by-同舟云学术

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Trajectory Planning for A Massive Number of UAVs in the Environment with Static and Dynamic Obstacles: A Mean Field Game Approach

Published:2022-11 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Agents (ICA)
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Author:

Niu Zijia¹,Jin Yuxin¹,Yao Wang²,Zhang Xiao³,Ren Lu¹

Affiliation:

1. School of Mathematical Sciences, LMIB Beihang University,Beijing,China

2. Institute of Artificial Intelligence, LMIB, Beihang University,Beijing,China

3. School of Mathematical Sciences, LMIB, BDBC Beihang University,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9999063/9999072/09999107.pdf?arnumber=9999107

Reference15 articles.

1. Energy-Efficient Velocity Control for Massive Numbers of UAVs: A Mean Field Game Approach

2. Massive Autonomous UAV Path Planning: A Neural Network Based Mean-Field Game Theoretic Approach

3. Alternating the population and control neural networks to solve high-dimensional stochastic mean-field games;lin;Proceedings of the National Academy of Sciences,2021

4. Mean field games

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1. Price-Based Offloading for Time-Sensitive and Thermal-Aware MEC Networks;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

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