Formation Control of Multi-quadrotors Based on Deep Q-learning-Reference-Cited by-同舟云学术

Formation Control of Multi-quadrotors Based on Deep Q-learning

Published:2022-11-15 Issue: Volume: Page:
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Container-title:2022 10th RSI International Conference on Robotics and Mechatronics (ICRoM)
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Author:

Mousavifard Roujin¹,Alipour Khalil¹,Najafqolian Mohammad Amin¹,Zarafshan Payam²

Affiliation:

1. University of Tehran,Advanced Service Robots (ASR) Laboratory,Department of Mechatronics Engineering Faculty of New Sciences and Technologies,Tehran,Iran

2. University of Tehran,AGRicultural INteligent Systems (AGRINS) Laboratory,Department of Mechatronics Engineering, Faculty of New Sciences and Tech,Tehran,Iran

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10025024/10025031/10025251.pdf?arnumber=10025251

Reference21 articles.

1. Adaptive Control With Unknown System Dynamics Estimator for Quadrotor Attitude Tracking

2. Robust Adaptive Attitude Tracking on SO(3) With an Application to a Quadrotor UAV;lee;IEEE Transactions on Control Systems Technology,2013

3. Robust trajectory tracking control for quadrotors with uncertainties and delays

4. Nonlinear Synergetic Optimal Controllers

5. Reinforcement -learning for optimal tracking control of linear discrete-time systems with unknown dynamics

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