Maximum margin planning. - Nathan D. Ratliff; J. Andrew Bagnell; Martin Zinkevich (ICML, 2006)

Boosting Structured Prediction for Imitation Learning. - Nathan D. Ratliff; David M. Bradley; J. Andrew Bagnell; Joel E. Chestnutt (NIPS, 2006)

Imitation learning for locomotion and manipulation. - Nathan D. Ratliff; James A. Bagnell; Siddhartha S. Srinivasa (Humanoids, 2007)

Kernel Conjugate Gradient for Fast Kernel Machines. - Nathan D. Ratliff; J. Andrew Bagnell (IJCAI, 2007)

(Approximate) Subgradient Methods for Structured Prediction. - Nathan D. Ratliff; J. Andrew Bagnell; Martin Zinkevich (AISTATS, 2007)

BiSpace Planning: Concurrent Multi-Space Exploration. - Rosen Diankov; Nathan D. Ratliff; Dave Ferguson 001; Siddhartha S. Srinivasa; James Kuffner (Robotics: Science and Systems, 2008)

CHOMP: Gradient optimization techniques for efficient motion planning. - Nathan D. Ratliff; Matthew Zucker 001; J. Andrew Bagnell; Siddhartha S. Srinivasa (ICRA, 2009)

Self-Supervised Aerial Image Analysis for Extracting Parking Lot Structure. - Young-Woo Seo; Nathan D. Ratliff; Chris Urmson (IJCAI, 2009)

Planning-based prediction for pedestrians. - Brian D. Ziebart; Nathan D. Ratliff; Garratt Gallagher; Christoph Mertz; Kevin M. Peterson; James A. Bagnell; Martial Hebert; Anind K. Dey; Siddhartha S. Srinivasa (IROS, 2009)

Learning to search: Functional gradient techniques for imitation learning. - Nathan D. Ratliff; David Silver; J. Andrew Bagnell (Auton. Robots, 2009)

Inverse Optimal Heuristic Control for Imitation Learning. - Nathan D. Ratliff; Brian D. Ziebart; Kevin M. Peterson; J. Andrew Bagnell; Martial Hebert; Anind K. Dey; Siddhartha S. Srinivasa (AISTATS, 2009)

Manipulation planning with goal sets using constrained trajectory optimization. - Anca D. Dragan; Nathan D. Ratliff; Siddhartha S. Srinivasa (ICRA, 2011)

Semi-supervised Learning with Density Based Distances. - Avleen Singh Bijral; Nathan D. Ratliff; Nathan Srebro (UAI, 2011)

Optimization and learning for rough terrain legged locomotion. - Matthew Zucker 001; Nathan D. Ratliff; Martin Stolle; Joel E. Chestnutt; J. Andrew Bagnell; Christopher G. Atkeson; James Kuffner (Int. J. Robotics Res., 2011)

CHOMP: Covariant Hamiltonian optimization for motion planning. - Matthew Zucker 001; Nathan D. Ratliff; Anca D. Dragan; Mihail Pivtoraiko; Matthew Klingensmith; Christopher M. Dellin; J. Andrew Bagnell; Siddhartha S. Srinivasa (Int. J. Robotics Res., 2013)

Dual execution of optimized contact interaction trajectories. - Marc Toussaint; Nathan D. Ratliff; Jeannette Bohg; Ludovic Righetti; Peter Englert; Stefan Schaal (IROS, 2014)

Understanding the geometry of workspace obstacles in Motion Optimization. - Nathan D. Ratliff; Marc Toussaint; Stefan Schaal (ICRA, 2015)

Direct Loss Minimization Inverse Optimal Control. - Andreas Doerr; Nathan D. Ratliff; Jeannette Bohg; Marc Toussaint; Stefan Schaal (Robotics: Science and Systems, 2015)

Policy Learning with Hypothesis based Local Action Selection. - Bharath Sankaran; Jeannette Bohg; Nathan D. Ratliff; Stefan Schaal (CoRR, 2015)

Warping the workspace geometry with electric potentials for motion optimization of manipulation tasks. - Jim Mainprice; Nathan D. Ratliff; Stefan Schaal (IROS, 2016)

Towards robust online inverse dynamics learning. - Franziska Meier; Daniel Kappler; Nathan D. Ratliff; Stefan Schaal (IROS, 2016)

DOOMED: Direct Online Optimization of Modeling Errors in Dynamics. - Nathan D. Ratliff; Franziska Meier; Daniel Kappler; Stefan Schaal (Big Data, 2016)

On the Fundamental Importance of Gauss-Newton in Motion Optimization. - Nathan D. Ratliff; Marc Toussaint; Jeannette Bohg; Stefan Schaal (CoRR, 2016)

A new data source for inverse dynamics learning. - Daniel Kappler; Franziska Meier; Nathan D. Ratliff; Stefan Schaal (IROS, 2017)

Real-time natural language corrections for assistive robotic manipulators. - Alexander Broad; Jacob Arkin; Nathan D. Ratliff; Thomas M. Howard; Brenna D. Argall (Int. J. Robotics Res., 2017)

RMPflow: A Computational Graph for Automatic Motion Policy Generation. - Ching-An Cheng; Mustafa Mukadam; Jan Issac; Stan Birchfield; Dieter Fox; Byron Boots; Nathan D. Ratliff (WAFR, 2018)

Riemannian Motion Policies. - Nathan D. Ratliff; Jan Issac; Daniel Kappler (CoRR, 2018)

RMPflow: A Computational Graph for Automatic Motion Policy Generation. - Ching-An Cheng; Mustafa Mukadam; Jan Issac; Stan Birchfield; Dieter Fox; Byron Boots; Nathan D. Ratliff (CoRR, 2018)

Real-Time Perception Meets Reactive Motion Generation. - Daniel Kappler; Franziska Meier; Jan Issac; Jim Mainprice; Cristina Garcia Cifuentes; Manuel Wuthrich; Vincent Berenz; Stefan Schaal; Nathan D. Ratliff; Jeannette Bohg (IEEE Robotics Autom. Lett., 2018)

Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. - Mustafa Mukadam; Ching-An Cheng; Dieter Fox; Byron Boots; Nathan D. Ratliff (CoRL, 2019)

Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations. - Muhammad Asif Rana; Anqi Li 001; Harish Ravichandar; Mustafa Mukadam; Sonia Chernova; Dieter Fox; Byron Boots; Nathan D. Ratliff (CoRL, 2019)

Predictor-Corrector Policy Optimization. - Ching-An Cheng; Xinyan Yan; Nathan D. Ratliff; Byron Boots (ICML, 2019)

Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience. - Yevgen Chebotar; Ankur Handa; Viktor Makoviychuk; Miles Macklin; Jan Issac; Nathan D. Ratliff; Dieter Fox (ICRA, 2019)

Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing. - Alexander Sasha Lambert; Mustafa Mukadam; Balakumar Sundaralingam; Nathan D. Ratliff; Byron Boots; Dieter Fox (ICRA, 2019)

Neural Autonomous Navigation with Riemannian Motion Policy. - Xiangyun Meng; Nathan D. Ratliff; Yu Xiang 001; Dieter Fox (ICRA, 2019)

Robust Learning of Tactile Force Estimation through Robot Interaction. - Balakumar Sundaralingam; Alexander Sasha Lambert; Ankur Handa; Byron Boots; Tucker Hermans; Stan Birchfield; Nathan D. Ratliff; Dieter Fox (ICRA, 2019)

Learning Latent Space Dynamics for Tactile Servoing. - Giovanni Sutanto; Nathan D. Ratliff; Balakumar Sundaralingam; Yevgen Chebotar; Zhe Su; Ankur Handa; Dieter Fox (ICRA, 2019)

Representing Robot Task Plans as Robust Logical-Dynamical Systems. - Chris Paxton 001; Nathan D. Ratliff; Clemens Eppner; Dieter Fox (IROS, 2019)

Trajectory Optimization for Coordinated Human-Robot Collaboration. - Adam Fishman; Chris Paxton 001; Wei Yang 019; Nathan D. Ratliff; Dieter Fox (CoRR, 2019)

DexPilot: Vision-Based Teleoperation of Dexterous Robotic Hand-Arm System. - Ankur Handa; Karl Van Wyk; Wei Yang 019; Jacky Liang; Yu-Wei Chao; Qian Wan; Stan Birchfield; Nathan D. Ratliff; Dieter Fox (ICRA, 2020)

Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. - Michelle A. Lee; Carlos Florensa; Jonathan Tremblay; Nathan D. Ratliff; Animesh Garg; Fabio Ramos 001; Dieter Fox (ICRA, 2020)

Scaling Local Control to Large-Scale Topological Navigation. - Xiangyun Meng; Nathan D. Ratliff; Yu Xiang 001; Dieter Fox (ICRA, 2020)

Collaborative Interaction Models for Optimized Human-Robot Teamwork. - Adam Fishman; Chris Paxton 001; Wei Yang 019; Dieter Fox; Byron Boots; Nathan D. Ratliff (IROS, 2020)

Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems. - Muhammad Asif Rana; Anqi Li 001; Dieter Fox; Byron Boots; Fabio Ramos 001; Nathan D. Ratliff (L4DC, 2020)

An Interior Point Method Solving Motion Planning Problems with Narrow Passages. - Jim Mainprice; Nathan D. Ratliff; Marc Toussaint; Stefan Schaal (RO-MAN, 2020)

RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies. - Ching-An Cheng; Mustafa Mukadam; Jan Issac; Stan Birchfield; Dieter Fox; Byron Boots; Nathan D. Ratliff (CoRR, 2020)

Optimization Fabrics. - Nathan D. Ratliff; Karl Van Wyk; Mandy Xie; Anqi Li 001; Muhammad Asif Rana (CoRR, 2020)

Geometric Fabrics for the Acceleration-based Design of Robotic Motion. - Mandy Xie; Karl Van Wyk; Anqi Li 001; Muhammad Asif Rana; Dieter Fox; Byron Boots; Nathan D. Ratliff (CoRR, 2020)

Optimization Fabrics for Behavioral Design. - Nathan D. Ratliff; Karl Van Wyk; Mandy Xie; Anqi Li; Muhammad Asif Rana (CoRR, 2020)

Model-Based Generalization Under Parameter Uncertainty Using Path Integral Control. - Ian Abraham; Ankur Handa; Nathan D. Ratliff; Kendall Lowrey; Todd D. Murphey; Dieter Fox (IEEE Robotics Autom. Lett., 2020)

STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation. - Mohak Bhardwaj; Balakumar Sundaralingam; Arsalan Mousavian; Nathan D. Ratliff; Dieter Fox; Fabio Ramos 001; Byron Boots (CoRL, 2021)

Generalized Nonlinear and Finsler Geometry for Robotics. - Nathan D. Ratliff; Karl Van Wyk; Mandy Xie; Anqi Li 001; Muhammad Asif Rana (ICRA, 2021)

Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees. - Muhammad Asif Rana; Anqi Li 001; Dieter Fox; Sonia Chernova; Byron Boots; Nathan D. Ratliff (IROS, 2021)

RMP2: A Structured Composable Policy Class for Robot Learning. - Anqi Li 001; Ching-An Cheng; Muhammad Asif Rana; Man Xie; Karl Van Wyk; Nathan D. Ratliff; Byron Boots (Robotics: Science and Systems, 2021)

Fast Joint Space Model-Predictive Control for Reactive Manipulation. - Mohak Bhardwaj; Balakumar Sundaralingam; Arsalan Mousavian; Nathan D. Ratliff; Dieter Fox; Fabio Ramos 001; Byron Boots (CoRR, 2021)

CoDE: Collocation for Demonstration Encoding. - Mandy Xie; Anqi Li; Karl Van Wyk; Frank Dellaert; Byron Boots; Nathan D. Ratliff (CoRR, 2021)

RMPflow: A Geometric Framework for Generation of Multitask Motion Policies. - Ching-An Cheng; Mustafa Mukadam; Jan Issac; Stan Birchfield; Dieter Fox; Byron Boots; Nathan D. Ratliff (IEEE Trans Autom. Sci. Eng., 2021)

Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration. - Mandy Xie; Ankur Handa; Stephen Tyree; Dieter Fox; Harish Ravichandar; Nathan D. Ratliff; Karl Van Wyk (CoRL, 2022)

Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior. - Karl Van Wyk; Mandy Xie; Anqi Li 001; Muhammad Asif Rana; Buck Babich; Bryan Peele; Qian Wan; Iretiayo Akinola; Balakumar Sundaralingam; Dieter Fox; Byron Boots; Nathan D. Ratliff (IEEE Robotics Autom. Lett., 2022)

CuRobo: Parallelized Collision-Free Robot Motion Generation. - Balakumar Sundaralingam; Siva Kumar Sastry Hari; Adam Fishman; Caelan Reed Garrett; Karl Van Wyk; Valts Blukis; Alexander Millane; Helen Oleynikova; Ankur Handa; Fabio Ramos 001; Nathan D. Ratliff; Dieter Fox (ICRA, 2023)

Global and Reactive Motion Generation with Geometric Fabric Command Sequences. - Weiming Zhi; Iretiayo Akinola; Karl Van Wyk; Nathan D. Ratliff; Fabio Ramos 001 (ICRA, 2023)

Fabrics: A Foundationally Stable Medium for Encoding Prior Experience. - Nathan D. Ratliff; Karl Van Wyk (CoRR, 2023)

CuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation. - Balakumar Sundaralingam; Siva Kumar Sastry Hari; Adam Fishman; Caelan Reed Garrett; Karl Van Wyk; Valts Blukis; Alexander Millane; Helen Oleynikova; Ankur Handa; Fabio Ramos 001; Nathan D. Ratliff; Dieter Fox (CoRR, 2023)

DextrAH-G: Pixels-to-Action Dexterous Arm-Hand Grasping with Geometric Fabrics. - Tyler Ga Wei Lum; Martin Matak; Viktor Makoviychuk; Ankur Handa; Arthur Allshire; Tucker Hermans; Nathan D. Ratliff; Karl Van Wyk (CoRL, 2024)

Geometric Fabrics: a Safe Guiding Medium for Policy Learning. - Karl Van Wyk; Ankur Handa; Viktor Makoviychuk; Yijie Guo; Arthur Allshire; Nathan D. Ratliff (ICRA, 2024)

Synthetica: Large Scale Synthetic Data for Robot Perception. - Ritvik Singh; Jingzhou Liu; Karl Van Wyk; Yu-Wei Chao; Jean-Francois Lafleche; Florian Shkurti; Nathan D. Ratliff; Ankur Handa (CoRR, 2024)

DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands. - Ritvik Singh; Arthur Allshire; Ankur Handa; Nathan D. Ratliff; Karl Van Wyk (CoRR, 2024)