Nathan Ratliff
Nathan Ratliff
Research Scientist, Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Title
Cited by
Cited by
Year
CHOMP: Gradient optimization techniques for efficient motion planning
N Ratliff, M Zucker, JA Bagnell, S Srinivasa
2009 IEEE International Conference on Robotics and Automation, 489-494, 2009
6462009
Maximum margin planning
ND Ratliff, JA Bagnell, MA Zinkevich
Proceedings of the 23rd international conference on Machine learning, 729-736, 2006
6022006
Planning-based prediction for pedestrians
BD Ziebart, N Ratliff, G Gallagher, C Mertz, K Peterson, JA Bagnell, ...
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems†…, 2009
4422009
Chomp: Covariant hamiltonian optimization for motion planning
M Zucker, N Ratliff, AD Dragan, M Pivtoraiko, M Klingensmith, CM Dellin, ...
The International Journal of Robotics Research 32 (9-10), 1164-1193, 2013
4142013
Learning to search: structured prediction techniques for imitation learning
ND Ratliff
Carnegie Mellon University, 2009
241*2009
Learning to search: Functional gradient techniques for imitation learning
ND Ratliff, D Silver, JA Bagnell
Autonomous Robots 27 (1), 25-53, 2009
2172009
Boosting structured prediction for imitation learning
J Bagnell, J Chestnutt, D Bradley, N Ratliff
Advances in Neural Information Processing Systems 19, 1153-1160, 2006
1582006
Closing the sim-to-real loop: Adapting simulation randomization with real world experience
Y Chebotar, A Handa, V Makoviychuk, M Macklin, J Issac, N Ratliff, D Fox
2019 International Conference on Robotics and Automation (ICRA), 8973-8979, 2019
1552019
Bispace planning: Concurrent multi-space exploration
R Diankov, N Ratliff, D Ferguson, S Srinivasa, J Kuffner
Proceedings of robotics: Science and systems IV 63, 2008
1252008
Imitation learning for locomotion and manipulation
N Ratliff, JA Bagnell, SS Srinivasa
2007 7th IEEE-RAS International Conference on Humanoid Robots, 392-397, 2007
1042007
(Approximate) Subgradient Methods for Structured Prediction
ND Ratliff, JA Bagnell, MA Zinkevich
Artificial Intelligence and Statistics, 380-387, 2007
982007
(Approximate) Subgradient Methods for Structured Prediction
ND Ratliff, JA Bagnell, MA Zinkevich
Artificial Intelligence and Statistics, 380-387, 2007
982007
Optimization and learning for rough terrain legged locomotion
M Zucker, N Ratliff, M Stolle, J Chestnutt, JA Bagnell, CG Atkeson, ...
The International Journal of Robotics Research 30 (2), 175-191, 2011
922011
Percutaneous intracerebral navigation by duty-cycled spinning of flexible bevel-tipped needles
JA Engh, DS Minhas, D Kondziolka, CN Riviere
Neurosurgery 67 (4), 1117-1123, 2010
682010
Manipulation planning with goal sets using constrained trajectory optimization
AD Dragan, ND Ratliff, SS Srinivasa
2011 IEEE International Conference on Robotics and Automation, 4582-4588, 2011
652011
Subgradient methods for maximum margin structured learning
N Ratliff, JA Bagnell, M Zinkevich
ICML workshop on learning in structured output spaces 46, 2006
552006
The effects of repeated exposure on liking and judgments of musical unity of intact and patchwork compositions
SL Tan, MP Spackman, CL Peaslee
Music Perception 23 (5), 407-421, 2006
502006
Inverse optimal heuristic control for imitation learning
N Ratliff, B Ziebart, K Peterson, JA Bagnell, M Hebert, AK Dey, S Srinivasa
Artificial Intelligence and Statistics, 424-431, 2009
492009
Understanding the geometry of workspace obstacles in motion optimization
N Ratliff, M Toussaint, S Schaal
2015 IEEE International Conference on Robotics and Automation (ICRA), 4202-4209, 2015
412015
Real-time perception meets reactive motion generation
D Kappler, F Meier, J Issac, J Mainprice, CG Cifuentes, M WŁthrich, ...
IEEE Robotics and Automation Letters 3 (3), 1864-1871, 2018
372018
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