2021
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Learning a State Representation and Navigation inCluttered and Dynamic Environments [Paper][Note]
- David Hoeller, Lorenz Wellhausen, Farbod Farshidian, Marco Hutter
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Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion [Paper][Note]
- Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai
2020
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MPC-based Controller with Terrain Insight for Dynamic Legged Locomotion [Paper][Note]
- Octavio Villarreal, Victor Barasuol
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Perceptive Locomotion in Rough Terrain - Online Foothold Optimization [Paper][Note]
- Fabian Jenelten, Takahiro Miki, Aravind E Vijayan, Marko Bjelonic, and Marco Hutter
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Multi-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control [Paper][Note]
- Ruben Grandia, Andrew J. Taylor, Aaron D. Ames, Marco Hutter
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Learning Variable Impedance Control forContact Sensitive Tasks [Paper][Note]
- Miroslav Bogdanovic, Majid Khadiv, Ludovic Righetti
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DeepQ Stepper: A framework for reactive dynamic walking on uneven terrain [Paper][Note]
- Avadesh Meduri, Majid Khadiv, Ludovic Righetti
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Practical Reinforcement Learning for MPC: Learning from sparse objectives in under an hour on a real robot [Paper][Note]
- Napat Karnchanachari, Miguel I. Valls, David Hoeller, Marco Hutter
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DeepGait: Planning and Control of Quadrupedal Gaits Using Deep Reinforcement Learning [Paper] [Note]
- Vassilios Tsounis, Mitja Alge, Joonho Lee, Farbod Farshidian, and Marco Hutter
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Learning quadrupedal locomotion over challenging terrain [Paper] [Note]
- JOONHO LEE, JEMIN HWANGBO
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Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion [Paper] [Note]
- Zhaoming Xie, Xingye Da
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Learning Agile Robotic Locomotion Skills by Imitating Animals [Paper] [Note]
- Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Edward Lee, Jie Tan, Sergey Levine
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C-CROC: Continuous and Convex Resolution of Centroidal Dynamic Trajectories for Legged Robots in Multicontact Scenarios [Paper] [Note]
- ierre Fernbach, Steve Tonneau
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Multi-expert learning of adaptive legged locomotion [Paper] [Note]
- Chuanyu Yang, Kai Yuan, Zhibin Li
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Learning to Walk in the Real World with Minimal Human Effort [Paper] [Note]
- Sehoon Ha, Peng Xu, Sergey Levine, Jie Tan
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Data Efficient Reinforcement Learning for Legged Robots [Paper] [Note]
- Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
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MPC-Net: A First Principle Guided Policy Search [Paper] [Note]
- Jan Carius, Farbod Farshidian, Marco Hutter
2019
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Fast and Continuous Foothold Adaptation for Dynamic Locomotion Through CNNs [Paper][Note]
- Octavio Antonio Villarreal Magana, Victor Barasuol, Marco Camurri
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Robust Recovery Controller for a QuadrupedalRobot using Deep Reinforcement Learning [Paper] [Note]
- Joonho Lee, Jemin Hwangbo, and Marco Hutter
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Learning to Walk via Deep Reinforcement Learning [Paper] [Note]
- Tuomas Haarnoja, Sehoon Ha
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Frequency-Aware Model Predictive Control [Paper][Note]
- Ruben Grandia, Farbod Farshidian, Alexey Dosovitskiy,Ren ́e Ranftl, and Marco Hutter
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Learning Agile and Dynamic Motor Skills for Legged Robots [Paper] [Note]
- JEMIN HWANGBO, JOONHO LEE
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Policy Transfer with Strategy Optimization [Paper] [Note]
- Wenhao Yu, C. Karen Liu, Greg Turk
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Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control [Paper] [Note]
- Donghyun Kim, Jared Di Carlo, Benjamin Katz, Gerardo Bledt, and Sangbae Kim
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Feedback MPC for Torque-Controlled Legged Robots [Paper] [Note]
- Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter
2018
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State Representation Learning for Control:An Overview [Paper] [Note]
- Timothée Lesort, David Filliat
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Robust Rough-Terrain Locomotion with a Quadrupedal Robot [Paper] [Note]
- Peter Fankhauser, Marko Bjelonic, C. Dario Bellicoso, Takahiro Miki and Marco Hutter
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Learning Sampling Distributions for Robot Motion Planning [Paper] [Note]
- Brian Ichter, James Harrison, Marco Pavone
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Sim-to-Real: Learning Agile Locomotion For Quadruped Robots [Paper] [Note]
- Jie Tan, Tingnan Zhang, Erwin Coumans, Atil Iscen
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Policies Modulating Trajectory Generators [Paper] [Note]
- Atil Iscen, Ken Caluwaerts, Erwin Coumans, Jie Tan
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Dynamic Locomotion in the MIT Cheetah 3 Through Convex Model-Predictive Control [Paper] [Note]
- Jared Di Carlo, Patrick M. Wensing
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Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupeds [Paper] [Note]
- Michael Neunert, Markus Stäuble , Markus Giftthaler , Carmine D. Bellicoso
2017
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Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter? [Paper] [Note]
- Xue Bin Peng, Michiel van de Panne
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Policy-Regularized Model Predictive Control to Stabilize Diverse Quadrupedal Gaits for the MIT Cheetah [Paper] [Note]
- Gerardo Bledt, Patrick M. Wensing, and Sangbae Kim
Before 2016