Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork-Reference-Cited by-同舟云学术

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Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork

Published:2020-11 Issue:11 Volume:33 Page:2930-2945
ISSN:1000-9361
Container-title:Chinese Journal of Aeronautics
language:en
Short-container-title:Chinese Journal of Aeronautics

Author:

WANG Chang,WU Lizhen,YAN Chao,WANG Zhichao,LONG Han,YU Chao

Funder

National Natural Science Foundation of China

National Key Laboratory of Science and Technology on UAV

Northwestern Polytechnical University

Publisher

Elsevier BV

Subject

Mechanical Engineering,Aerospace Engineering

Reference45 articles.

1. Handbook of research on design, control, and modeling of swarm robotics,2015

2. A survey on aerial swarm robotics;Chung;IEEE Trans Rob,2018

3. Multi-agent systems: A survey;Dorri;IEEE Access,2018

4. Schmitt M, Stuetz P. Cooperative multi-UAV sensor and perception management for helicopter landing zone Reconnaissance: Implementation and experimental evaluation. AIAA scitech 2019 forum; 2019.

5. Multi-agent distributed coordination control: Developments and directions via graph viewpoint;Wang;Neurocomputing,2016

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