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Quadrotors are among the most agile flying robots.
Helicopter performance, stability, and control
Raymond W Prouty · 1995
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Vision based mav navigation in unknown and unstructured environments
Michael Bloesch, Stephan Weiss, Davide Scaramuzza, and Roland Siegwart · 2010
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Vision-based state estimation and trajectory control towards high-speed flight with a quadrotor
Shaojie Shen, Yash Mulgaonkar, Nathan Michael, and Vijay Kumar · 2013
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Unified temporal and spatial calibration for multi-sensor systems
Paul Furgale, Joern Rehder, and Roland Siegwart · 2013
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The arcade learning environment: An evaluation platform for general agents
M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling · 2013
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Rolling shutter camera calibration
Luc Oth, Paul Furgale, Laurent Kneip, and Roland Siegwart · 2013
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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High speed navigation for quadrotors with limited onboard sensing
Sikang Liu, M. Watterson, S. Tang, and V. Kumar · 2016
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Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis · 2016
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
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Cad2rl: Real single-image flight without a single real image
Fereshteh Sadeghi and Sergey Levine · 2016
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Estimation, control, and planning for aggressive flight with a small quadrotor with a single camera and IMU
G. Loianno, C. Brunner, G. McGrath, and V. Kumar · 2017
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Aggressive quadrotor flight through narrow gaps with onboard sensing and computing using active vision
Davide Falanga, Elias Mueggler, Matthias Faessler, and Davide Scaramuzza · 2017
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CAD2RL: Real single-image flight without a single real image
Fereshteh Sadeghi and Sergey Levine · 2017
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DeepVO: Towards end-to-end visual odometry with deep recurrent convolutional neural networks
Sen Wang, Ronald Clark, Hongkai Wen, and Niki Trigoni · 2017
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Sim-to-real robot learning from pixels with progressive nets
Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, and Raia Hadsell · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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Propeller thrust and drag in forward flight
Rajan Gill and Raffaello D’Andrea · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Fast, autonomous flight in gps-denied and cluttered environments
Kartik Mohta, Michael Watterson, Yash Mulgaonkar, Sikang Liu, Chao Qu, Anurag Makineni, Kelsey Saulnier, Ke Sun, Alex Zhu, Jeffrey Delmerico, Konstantinos Karydis, Nikolay Atanasov, Giuseppe Loianno, Davide Scaramuzza, Kostas Daniilidis, Camillo Jose Taylor, and Vijay Kumar · 2018
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Autonomous aerial navigation using monocular visual-inertial fusion
Yi Lin, Fei Gao, Tong Qin, Wenliang Gao, Tianbo Liu, William Wu, Zhenfei Yang, and Shaojie Shen · 2018
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Dronet: Learning to fly by driving
Antonio Loquercio, Ana I Maqueda, Carlos R Del-Blanco, and Davide Scaramuzza · 2018
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DeepMind Control Suite, January 2018
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, and Martin Riedmiller · 2018
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Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Zachary Teed and Jia Deng · 2021
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Improving sample efficiency in model-free reinforcement learning from images
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, and Rob Fergus · 2021
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Human-piloted drone racing: Visual processing and control
Christian Pfeiffer and Davide Scaramuzza · 2021
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Neurobem: Hybrid aerodynamic quadrotor model
Leonard Bauersfeld, Elia Kaufmann, Philipp Foehn, Sihao Sun, and Davide Scaramuzza · 2021
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Understanding catastrophic forgetting and remembering in continual learning with optimal relevance mapping, 2021
Prakhar Kaushik, Alex Gain, Adam Kortylewski, and Alan Yuille · 2021
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Rapid locomotion via reinforcement learning
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Deep drone racing: Learning agile flight in dynamic environments
Elia Kaufmann, Antonio Loquercio, Rene Ranftl, Alexey Dosovitskiy, Vladlen Koltun, and Davide Scaramuzza · 2018
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The double sphere camera model
Vladyslav C. Usenko, Nikolaus Demmel, and Daniel Cremers · 2018
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Learning latent dynamics for planning from pixels
Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2019
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Reinforcement learning for uav attitude control
William Koch, Renato Mancuso, Richard West, and Azer Bestavros · 2019
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Low-level control of a quadrotor with deep model-based reinforcement learning
Nathan O Lambert, Daniel S Drew, Joseph Yaconelli, Sergey Levine, Roberto Calandra, and Kristofer SJ Pister · 2019
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On the continuity of rotation representations in neural networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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Special issue on future challenges and opportunities in vision-based drone navigation
Giuseppe Loianno and Davide Scaramuzza · 2020
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Gabriel Margolis, Ge Yang, Kartik Paigwar, Tao Chen, and Pulkit Agrawal · 2022
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Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, and Marco Hutter · 2022
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Zachary Teed, Lahav Lipson, and Jia Deng · 2022
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Swin transformer v2: Scaling up capacity and resolution
Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, and Baining Guo · 2022
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Mastering visual continuous control: Improved data-augmented reinforcement learning
Denis Yarats, Rob Fergus, Alessandro Lazaric, and Lerrel Pinto · 2022
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Daydreamer: World models for physical robot learning
Philipp Wu, Alejandro Escontrela, Danijar Hafner, Pieter Abbeel, and Ken Goldberg · 2022
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A benchmark comparison of learned control policies for agile quadrotor flight
Elia Kaufmann, Leonard Bauersfeld, and Davide Scaramuzza · 2022
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Champion-level drone racing using deep reinforcement learning
Elia Kaufmann, Leonard Bauersfeld, Antonio Loquercio, Matthias Müller, Vladlen Koltun, and Davide Scaramuzza · 2023
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Deep whole-body control: Learning a unified policy for manipulation and locomotion
Zipeng Fu, Xuxin Cheng, and Deepak Pathak · 2023
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NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration
Ajay Sridhar, Dhruv Shah, Catherine Glossop, and Sergey Levine · 2023
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End-to-end reinforcement learning for time-optimal quadcopter flight
Robin Ferede, Christophe De Wagter, Dario Izzo, and Guido CHE de Croon · 2023
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Learning to fly in seconds
Jonas Eschmann, Dario Albani, and Giuseppe Loianno · 2023
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Contrastive initial state buffer for reinforcement learning, 2023
Nico Messikommer, Yunlong Song, and Davide Scaramuzza · 2023
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Mobile aloha: Learning bimanual mobile manipulation with low-cost whole-body teleoperation
Zipeng Fu, Tony Z. Zhao, and Chelsea Finn · 2024
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