Nathan D. Ratliff

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 68

Top Topics

Dynamical Systems

Robotic Manipulator

Inverse Dynamics

Top Venues

Publications

Karl Van Wyk, Ankur Handa, Viktor Makoviychuk, Yijie Guo, Arthur Allshire, Nathan D. Ratliff
Geometric Fabrics: a Safe Guiding Medium for Policy Learning. ICRA (2024)
Karl Van Wyk, Ankur Handa, Viktor Makoviychuk, Yijie Guo, Arthur Allshire, Nathan D. Ratliff
Geometric Fabrics: a Safe Guiding Medium for Policy Learning. CoRR (2024)
Tyler Ga Wei Lum, Martin Matak, Viktor Makoviychuk, Ankur Handa, Arthur Allshire, Tucker Hermans, Nathan D. Ratliff, Karl Van Wyk
DextrAH-G: Pixels-to-Action Dexterous Arm-Hand Grasping with Geometric Fabrics. CoRR (2024)
Balakumar Sundaralingam, Siva Kumar Sastry Hari, Adam Fishman, Caelan Reed Garrett, Karl Van Wyk, Valts Blukis, Alexander Millane, Helen Oleynikova, Ankur Handa, Fabio Ramos, Nathan D. Ratliff, Dieter Fox
CuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation. CoRR (2023)
Nathan D. Ratliff, Karl Van Wyk
Fabrics: A Foundationally Stable Medium for Encoding Prior Experience. CoRR (2023)
Balakumar Sundaralingam, Siva Kumar Sastry Hari, Adam Fishman, Caelan Reed Garrett, Karl Van Wyk, Valts Blukis, Alexander Millane, Helen Oleynikova, Ankur Handa, Fabio Ramos, Nathan D. Ratliff, Dieter Fox
CuRobo: Parallelized Collision-Free Robot Motion Generation. ICRA (2023)
Weiming Zhi, Iretiayo Akinola, Karl Van Wyk, Nathan D. Ratliff, Fabio Ramos
Global and Reactive Motion Generation with Geometric Fabric Command Sequences. ICRA (2023)
Mandy Xie, Ankur Handa, Stephen Tyree, Dieter Fox, Harish Ravichandar, Nathan D. Ratliff, Karl Van Wyk
Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration. CoRL (2022)
Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana, Buck Babich, Bryan Peele, Qian Wan, Iretiayo Akinola, Balakumar Sundaralingam, Dieter Fox, Byron Boots, Nathan D. Ratliff
Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior. IEEE Robotics Autom. Lett. 7 (2) (2022)
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RMP2: A Structured Composable Policy Class for Robot Learning. Robotics: Science and Systems (2021)
Mandy Xie, Anqi Li, Karl Van Wyk, Frank Dellaert, Byron Boots, Nathan D. Ratliff
CoDE: Collocation for Demonstration Encoding. CoRR (2021)
Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana, Buck Babich, Bryan Peele, Qian Wan, Iretiayo Akinola, Balakumar Sundaralingam, Dieter Fox, Byron Boots, Nathan D. Ratliff
Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior. CoRR (2021)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Geometric Framework for Generation of Multitask Motion Policies. IEEE Trans Autom. Sci. Eng. 18 (3) (2021)
M. Asif Rana, Anqi Li, Dieter Fox, Sonia Chernova, Byron Boots, Nathan D. Ratliff
Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees. IROS (2021)
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana
Generalized Nonlinear and Finsler Geometry for Robotics. ICRA (2021)
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RMP2: A Structured Composable Policy Class for Robot Learning. CoRR (2021)
Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation. CoRL (2021)
Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots
Fast Joint Space Model-Predictive Control for Reactive Manipulation. CoRR (2021)
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. ICRA (2020)
Mandy Xie, Karl Van Wyk, Anqi Li, Muhammad Asif Rana, Dieter Fox, Byron Boots, Nathan D. Ratliff
Geometric Fabrics for the Acceleration-based Design of Robotic Motion. CoRR (2020)
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana
Generalized Nonlinear and Finsler Geometry for Robotics. CoRR (2020)
Ian Abraham, Ankur Handa, Nathan D. Ratliff, Kendall Lowrey, Todd D. Murphey, Dieter Fox
Model-Based Generalization Under Parameter Uncertainty Using Path Integral Control. CoRR (2020)
Adam Fishman, Chris Paxton, Wei Yang, Dieter Fox, Byron Boots, Nathan D. Ratliff
Collaborative Interaction Models for Optimized Human-Robot Teamwork. IROS (2020)
Jim Mainprice, Nathan D. Ratliff, Marc Toussaint, Stefan Schaal
An Interior Point Method Solving Motion Planning Problems with Narrow Passages. CoRR (2020)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies. CoRR (2020)
Jim Mainprice, Nathan D. Ratliff, Marc Toussaint, Stefan Schaal
An Interior Point Method Solving Motion Planning Problems with Narrow Passages. RO-MAN (2020)
Ankur Handa, Karl Van Wyk, Wei Yang, Jacky Liang, Yu-Wei Chao, Qian Wan, Stan Birchfield, Nathan D. Ratliff, Dieter Fox
DexPilot: Vision-Based Teleoperation of Dexterous Robotic Hand-Arm System. ICRA (2020)
Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan D. Ratliff
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems. L4DC (2020)
Ian Abraham, Ankur Handa, Nathan D. Ratliff, Kendall Lowrey, Todd D. Murphey, Dieter Fox
Model-Based Generalization Under Parameter Uncertainty Using Path Integral Control. IEEE Robotics Autom. Lett. 5 (2) (2020)
Muhammad Asif Rana, Anqi Li, Dieter Fox, Sonia Chernova, Byron Boots, Nathan D. Ratliff
Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees. CoRR (2020)
Xiangyun Meng, Nathan D. Ratliff, Yu Xiang, Dieter Fox
Scaling Local Control to Large-Scale Topological Navigation. ICRA (2020)
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. CoRR (2020)
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana
Optimization Fabrics. CoRR (2020)
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, Muhammad Asif Rana
Optimization Fabrics for Behavioral Design. CoRR (2020)
Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan D. Ratliff
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems. CoRR (2020)
Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRL (2019)
Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
Predictor-Corrector Policy Optimization. ICML (2019)
Chris Paxton, Nathan D. Ratliff, Clemens Eppner, Dieter Fox
Representing Robot Task Plans as Robust Logical-Dynamical Systems. IROS (2019)
Alexander Lambert, Mustafa Mukadam, Balakumar Sundaralingam, Nathan D. Ratliff, Byron Boots, Dieter Fox
Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing. CoRR (2019)
Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRR (2019)
Xiangyun Meng, Nathan D. Ratliff, Yu Xiang, Dieter Fox
Scaling Local Control to Large-Scale Topological Navigation. CoRR (2019)
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk, Miles Macklin, Jan Issac, Nathan D. Ratliff, Dieter Fox
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience. ICRA (2019)
Adam Fishman, Chris Paxton, Wei Yang, Nathan D. Ratliff, Dieter Fox
Trajectory Optimization for Coordinated Human-Robot Collaboration. CoRR (2019)
Xiangyun Meng, Nathan D. Ratliff, Yu Xiang, Dieter Fox
Neural Autonomous Navigation with Riemannian Motion Policy. CoRR (2019)
Chris Paxton, Nathan D. Ratliff, Clemens Eppner, Dieter Fox
Representing Robot Task Plans as Robust Logical-Dynamical Systems. CoRR (2019)
Ankur Handa, Karl Van Wyk, Wei Yang, Jacky Liang, Yu-Wei Chao, Qian Wan, Stan Birchfield, Nathan D. Ratliff, Dieter Fox
DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System. CoRR (2019)
Muhammad Asif Rana, Anqi Li, Harish Ravichandar, Mustafa Mukadam, Sonia Chernova, Dieter Fox, Byron Boots, Nathan D. Ratliff
Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations. CoRL (2019)
Xiangyun Meng, Nathan D. Ratliff, Yu Xiang, Dieter Fox
Neural Autonomous Navigation with Riemannian Motion Policy. ICRA (2019)
Giovanni Sutanto, Nathan D. Ratliff, Balakumar Sundaralingam, Yevgen Chebotar, Zhe Su, Ankur Handa, Dieter Fox
Learning Latent Space Dynamics for Tactile Servoing. ICRA (2019)
Alexander Sasha Lambert, Mustafa Mukadam, Balakumar Sundaralingam, Nathan D. Ratliff, Byron Boots, Dieter Fox
Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing. ICRA (2019)
Balakumar Sundaralingam, Alexander Sasha Lambert, Ankur Handa, Byron Boots, Tucker Hermans, Stan Birchfield, Nathan D. Ratliff, Dieter Fox
Robust Learning of Tactile Force Estimation through Robot Interaction. ICRA (2019)
Balakumar Sundaralingam, Alexander Sasha Lambert, Ankur Handa, Byron Boots, Tucker Hermans, Stan Birchfield, Nathan D. Ratliff, Dieter Fox
Robust Learning of Tactile Force Estimation through Robot Interaction. CoRR (2018)
Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
Predictor-Corrector Policy Optimization. CoRR (2018)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Computational Graph for Automatic Motion Policy Generation. CoRR (2018)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
: A Computational Graph for Automatic Motion Policy Generation. WAFR (2018)
Nathan D. Ratliff, Jan Issac, Daniel Kappler
Riemannian Motion Policies. CoRR (2018)
Daniel Kappler, Franziska Meier, Jan Issac, Jim Mainprice, Cristina Garcia Cifuentes, Manuel Wuthrich, Vincent Berenz, Stefan Schaal, Nathan D. Ratliff, Jeannette Bohg
Real-Time Perception Meets Reactive Motion Generation. IEEE Robotics Autom. Lett. 3 (3) (2018)
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk, Miles Macklin, Jan Issac, Nathan D. Ratliff, Dieter Fox
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience. CoRR (2018)
Giovanni Sutanto, Nathan D. Ratliff, Balakumar Sundaralingam, Yevgen Chebotar, Zhe Su, Ankur Handa, Dieter Fox
Learning Latent Space Dynamics for Tactile Servoing. CoRR (2018)
Daniel Kappler, Franziska Meier, Nathan D. Ratliff, Stefan Schaal
A New Data Source for Inverse Dynamics Learning. CoRR (2017)
Daniel Kappler, Franziska Meier, Nathan D. Ratliff, Stefan Schaal
A new data source for inverse dynamics learning. IROS (2017)
Daniel Kappler, Franziska Meier, Jan Issac, Jim Mainprice, Cristina Garcia Cifuentes, Manuel Wüthrich, Vincent Berenz, Stefan Schaal, Nathan D. Ratliff, Jeannette Bohg
Real-time Perception meets Reactive Motion Generation. CoRR (2017)
Alexander Broad, Jacob Arkin, Nathan D. Ratliff, Thomas M. Howard, Brenna D. Argall
Real-time natural language corrections for assistive robotic manipulators. Int. J. Robotics Res. 36 (5-7) (2017)
Nathan D. Ratliff, Franziska Meier, Daniel Kappler, Stefan Schaal
DOOMED: Direct Online Optimization of Modeling Errors in Dynamics. CoRR (2016)
Jim Mainprice, Nathan D. Ratliff, Stefan Schaal
Warping the workspace geometry with electric potentials for motion optimization of manipulation tasks. IROS (2016)
Franziska Meier, Daniel Kappler, Nathan D. Ratliff, Stefan Schaal
Towards robust online inverse dynamics learning. IROS (2016)
Nathan D. Ratliff, Marc Toussaint, Jeannette Bohg, Stefan Schaal
On the Fundamental Importance of Gauss-Newton in Motion Optimization. CoRR (2016)
Nathan D. Ratliff, Franziska Meier, Daniel Kappler, Stefan Schaal
DOOMED: Direct Online Optimization of Modeling Errors in Dynamics. Big Data 4 (4) (2016)
Bharath Sankaran, Jeannette Bohg, Nathan D. Ratliff, Stefan Schaal
Policy Learning with Hypothesis based Local Action Selection. CoRR (2015)
Nathan D. Ratliff, Marc Toussaint, Stefan Schaal
Understanding the geometry of workspace obstacles in Motion Optimization. ICRA (2015)
Andreas Doerr, Nathan D. Ratliff, Jeannette Bohg, Marc Toussaint, Stefan Schaal
Direct Loss Minimization Inverse Optimal Control. Robotics: Science and Systems (2015)
Marc Toussaint, Nathan D. Ratliff, Jeannette Bohg, Ludovic Righetti, Peter Englert, Stefan Schaal
Dual execution of optimized contact interaction trajectories. IROS (2014)
Matthew Zucker, Nathan D. Ratliff, Anca D. Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher M. Dellin, J. Andrew Bagnell, Siddhartha S. Srinivasa
CHOMP: Covariant Hamiltonian optimization for motion planning. Int. J. Robotics Res. 32 (9-10) (2013)
Avleen Singh Bijral, Nathan D. Ratliff, Nathan Srebro
Semi-supervised Learning with Density Based Distances CoRR (2012)
Avleen Singh Bijral, Nathan D. Ratliff, Nathan Srebro
Semi-supervised Learning with Density Based Distances. UAI (2011)
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, Joel E. Chestnutt, J. Andrew Bagnell, Christopher G. Atkeson, James Kuffner
Optimization and learning for rough terrain legged locomotion. Int. J. Robotics Res. 30 (2) (2011)
Anca D. Dragan, Nathan D. Ratliff, Siddhartha S. Srinivasa
Manipulation planning with goal sets using constrained trajectory optimization. ICRA (2011)
Nathan D. Ratliff, David Silver, J. Andrew Bagnell
Learning to search: Functional gradient techniques for imitation learning. Auton. Robots 27 (1) (2009)
Nathan D. Ratliff, Brian D. Ziebart, Kevin M. Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha S. Srinivasa
Inverse Optimal Heuristic Control for Imitation Learning. AISTATS (2009)
Young-Woo Seo, Nathan D. Ratliff, Chris Urmson
Self-Supervised Aerial Image Analysis for Extracting Parking Lot Structure. IJCAI (2009)
Brian D. Ziebart, Nathan D. Ratliff, Garratt Gallagher, Christoph Mertz, Kevin M. Peterson, James A. Bagnell, Martial Hebert, Anind K. Dey, Siddhartha S. Srinivasa
Planning-based prediction for pedestrians. IROS (2009)
Nathan D. Ratliff, Matthew Zucker, J. Andrew Bagnell, Siddhartha S. Srinivasa
CHOMP: Gradient optimization techniques for efficient motion planning. ICRA (2009)
Rosen Diankov, Nathan D. Ratliff, Dave Ferguson, Siddhartha S. Srinivasa, James Kuffner
BiSpace Planning: Concurrent Multi-Space Exploration. Robotics: Science and Systems (2008)
Nathan D. Ratliff, J. Andrew Bagnell
Kernel Conjugate Gradient for Fast Kernel Machines. IJCAI (2007)
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinkevich
(Approximate) Subgradient Methods for Structured Prediction. AISTATS (2007)
Nathan D. Ratliff, James A. Bagnell, Siddhartha S. Srinivasa
Imitation learning for locomotion and manipulation. Humanoids (2007)
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinkevich
Maximum margin planning. ICML (2006)
Nathan D. Ratliff, David M. Bradley, J. Andrew Bagnell, Joel E. Chestnutt
Boosting Structured Prediction for Imitation Learning. NIPS (2006)