Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms-Reference-Cited by-同舟云学术

Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms

Published:2023-04 Issue:4 Volume:8 Page:2397-2404
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Salzmann Tim¹^ORCID,Kaufmann Elia²^ORCID,Arrizabalaga Jon¹^ORCID,Pavone Marco³^ORCID,Scaramuzza Davide²^ORCID,Ryll Markus¹^ORCID

Affiliation:

1. Technical University of Munich, Munich, Germany

2. University of Zurich, Zurich, Switzerland

3. Stanford University and NVIDIA Research, Stanford, CA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10049284/10049101.pdf?arnumber=10049101

Reference34 articles.

1. Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control

2. A Neural Network Architecture to Learn Explicit MPC Controllers from Data

3. Agilicious: Open-source and open-hardware agile quadrotor for vision-based flight

4. On training and evaluation of neural network approaches for model predictive control;winqvist,2020

5. Model Predictive Control Using Artificial Neural Network for Power Converters

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