Aggressive Online Control of a Quadrotor via Deep Network Representations of Optimality Principles

D. Mellinger and V. Kumar, “Minimum snap trajectory generation and control for quadrotors,” in 2011 IEEE International Conference on Robotics and Automation

2011

Earlier work this paper cites.

M. Hehn and R. D’Andrea, “Quadrocopter trajectory generation and control,” IFAC proceedings Volumes

2011

Earlier work this paper cites.

M. Hehn, R. Ritz, and R. D’Andrea, “Performance benchmarking of quadrotor systems using time-optimal control,” Autonomous Robots

2012

Earlier work this paper cites.

E. J. Smeur, Q. Chu, and G. C. de Croon, “Adaptive incremental nonlinear dynamic inversion for attitude control of micro air vehicles,” Journal of Guidance, Control, and Dynamics

2015

Earlier work this paper cites.

A. Bry, C. Richter, A. Bachrach, and N. Roy, “Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments,” The International Journal of Robotics Research

2015

Earlier work this paper cites.

F. Morbidi, R. Cano, and D. Lara, “Minimum-energy path generation for a quadrotor uav,” in 2016 IEEE International Conference on Robotics and Automation (ICRA)

2016

Earlier work this paper cites.

O. Santos, H. Romero, S. Salazar, O. García-Pérez, and R. Lozano, “Optimized discrete control law for quadrotor stabilization: Experimental results,” Journal of Intelligent & Robotic Systems

2016

Cited alongside, same era.

M. Geisert and N. Mansard, “Trajectory generation for quadrotor based systems using numerical optimal control,” in 2016 IEEE international conference on robotics and automation (ICRA)

2016

Cited alongside, same era.

S. Li, Y. Wang, J. Tan, and Y. Zheng, “Adaptive rbfnns/integral sliding mode control for a quadrotor aircraft,” Neurocomputing

2016

Cited alongside, same era.

Q. Li, J. Qian, Z. Zhu, X. Bao, M. K. Helwa, and A. P. Schoellig, “Deep neural networks for improved, impromptu trajectory tracking of quadrotors,” in 2017 IEEE International Conference on Robotics and Automation (ICRA)

2017

Cited alongside, same era.

E. Tal and S. Karaman, “Accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness,” in 2018 IEEE Conference on Decision and Control (CDC)

2018

Later among the works it cites.

G. Tang, W. Sun, and K. Hauser, “Learning trajectories for real-time optimal control of quadrotors,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

2018

Later among the works it cites.

C. Sánchez-Sánchez and D. Izzo, “Real-time optimal control via deep neural networks: study on landing problems,” Journal of Guidance, Control, and Dynamics

2018

Later among the works it cites.

D. Izzo, D. Tailor, and T. Vasileiou, “On the stability analysis of deep neural network representations of an optimal state-feedback,” arXiv e-prints

Original

2018

Later among the works it cites.