Articles avec mandats d'accès public - Michael LaskeyEn savoir plus
Disponibles quelque part : 16
Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards
J Mahler, FT Pokorny, B Hou, M Roderick, M Laskey, M Aubry, K Kohlhoff, ...
2016 IEEE international conference on robotics and automation (ICRA), 1957-1964, 2016
Exigences : US National Science Foundation
Dart: Noise injection for robust imitation learning
M Laskey, J Lee, R Fox, A Dragan, K Goldberg
Conference on robot learning, 143-156, 2017
Exigences : US National Science Foundation
Learning rope manipulation policies using dense object descriptors trained on synthetic depth data
P Sundaresan, J Grannen, B Thananjeyan, A Balakrishna, M Laskey, ...
2020 IEEE International Conference on Robotics and Automation (ICRA), 9411-9418, 2020
Exigences : US National Science Foundation
Deep transfer learning of pick points on fabric for robot bed-making
D Seita, N Jamali, M Laskey, AK Tanwani, R Berenstein, P Baskaran, ...
The International Symposium of Robotics Research, 275-290, 2019
Exigences : US National Science Foundation
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations
M Laskey, J Lee, C Chuck, D Gealy, W Hsieh, FT Pokorny, AD Dragan, ...
2016 IEEE international conference on automation science and engineering …, 2016
Exigences : US National Science Foundation
Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces
M Laskey, S Staszak, WYS Hsieh, J Mahler, FT Pokorny, AD Dragan, ...
2016 IEEE International Conference on Robotics and Automation (ICRA), 462-469, 2016
Exigences : US National Science Foundation
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations
M Laskey, C Chuck, J Lee, J Mahler, S Krishnan, K Jamieson, A Dragan, ...
2017 IEEE International Conference on Robotics and Automation (ICRA), 358-365, 2017
Exigences : US Department of Defense
Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot
J Liang, J Mahler, M Laskey, P Li, K Goldberg
2017 13th IEEE Conference on Automation Science and Engineering (CASE), 1-8, 2017
Exigences : US National Science Foundation, US Department of Defense
Robot bed-making: Deep transfer learning using depth sensing of deformable fabric
D Seita, N Jamali, M Laskey, R Berenstein, AK Tanwani, P Baskaran, ...
arXiv preprint arXiv:1809.09810 26, 2018
Exigences : US National Science Foundation
Statistical data cleaning for deep learning of automation tasks from demonstrations
C Chuck, M Laskey, S Krishnan, R Joshi, R Fox, K Goldberg
2017 13th IEEE Conference on Automation Science and Engineering (CASE), 1142 …, 2017
Exigences : US National Science Foundation, US Department of Defense
Generalizing robot imitation learning with invariant hidden semi-markov models
AK Tanwani, J Lee, B Thananjeyan, M Laskey, S Krishnan, R Fox, ...
Algorithmic Foundations of Robotics XIII: Proceedings of the 13th Workshop …, 2020
Exigences : US National Science Foundation, European Commission
Dex-net mm: Deep grasping for surface decluttering with a low-precision mobile manipulator
B Staub, AK Tanwani, J Mahler, M Breyer, M Laskey, Y Takaoka, ...
2019 IEEE 15th International Conference on Automation Science and …, 2019
Exigences : US National Science Foundation
A dynamic regret analysis and adaptive regularization algorithm for on-policy robot imitation learning
JN Lee, M Laskey, AK Tanwani, A Aswani, K Goldberg
Algorithmic Foundations of Robotics XIII: Proceedings of the 13th Workshop …, 2020
Exigences : US National Science Foundation
Dynamic regret convergence analysis and an adaptive regularization algorithm for on-policy robot imitation learning
JN Lee, M Laskey, AK Tanwani, A Aswani, K Goldberg
The International Journal of Robotics Research 40 (10-11), 1284-1305, 2021
Exigences : US National Science Foundation
An algorithm and user study for teaching bilateral manipulation via iterated best response demonstrations
C Chen, S Krishnan, M Laskey, R Fox, K Goldberg
2017 13th IEEE Conference on Automation Science and Engineering (CASE), 151-158, 2017
Exigences : US National Science Foundation
Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations
J Lee, M Laskey, R Fox, K Goldberg
2018 IEEE 14th International Conference on Automation Science and …, 2018
Exigences : US National Science Foundation
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