A Novel Multivariate Skew-Normal Mixture Model and Its Application in Path-Planning for Very-Large-Scale Robotic Systems-Reference-Cited by-同舟云学术

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A Novel Multivariate Skew-Normal Mixture Model and Its Application in Path-Planning for Very-Large-Scale Robotic Systems

Published:2024-07-10 Issue: Volume:20 Page:3783-3790
ISSN:
Container-title:2024 American Control Conference (ACC)
language:
Short-container-title:

Author:

Zhu Pingping¹,Liu Chang²,Estephan Peter³

Affiliation:

1. Marshall University,Faculty of Computer Sciences and Electrical Engineering,Huntington,WV,USA

2. College of Engineering, Peking University,Department of Advanced Manufacturing and Robotics,Beijing,China,100871

3. Marshall University,Department of Computer Sciences and Electrical Engineering,Huntington,WV,USA

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10644130/10644150/10644239.pdf?arnumber=10644239

Reference20 articles.

1. Long duration autonomy for maritime systems: challenges and opportunities

2. Deep reinforcement learning for swarm systems;Hüttenrauch;Journal of Machine Learning Research,2019

3. A survey and critique of multiagent deep reinforcement learning

4. Multiple Mobile Robot Teams, Path Planning and Motion Coordination in

5. Distributed optimal control for multi-agent trajectory optimization

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