Michael Laskey
Michael Laskey
Toyota Research Institute
Verified email at berkeley.edu
Title
Cited by
Cited by
Year
Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics
J Mahler, J Liang, S Niyaz, M Laskey, R Doan, X Liu, JA Ojea, K Goldberg
arXiv preprint arXiv:1703.09312, 2017
3712017
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
1882016
Dart: Noise injection for robust imitation learning
M Laskey, J Lee, R Fox, A Dragan, K Goldberg
arXiv preprint arXiv:1703.09327, 2017
77*2017
Scaling up gaussian belief space planning through covariance-free trajectory optimization and automatic differentiation
S Patil, G Kahn, M Laskey, J Schulman, K Goldberg, P Abbeel
Algorithmic foundations of robotics XI, 515-533, 2015
702015
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and gaussian process regression
J Mahler, S Krishnan, M Laskey, S Sen, A Murali, B Kehoe, S Patil, ...
2014 IEEE International Conference on Automation Science and Engineering …, 2014
572014
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
532016
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
502016
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
452017
Multi-armed bandit models for 2d grasp planning with uncertainty
M Laskey, J Mahler, Z McCarthy, FT Pokorny, S Patil, J Van Den Berg, ...
2015 IEEE International Conference on Automation Science and Engineering …, 2015
332015
Deep transfer learning of pick points on fabric for robot bed-making
D Seita, N Jamali, M Laskey, AK Tanwani, R Berenstein, P Baskaran, ...
arXiv preprint arXiv:1809.09810, 2018
21*2018
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
132017
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
102017
Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics. arXiv 2017
J Mahler, J Liang, S Niyaz, M Laskey, R Doan, X Liu, JA Ojea, K Goldberg
arXiv preprint arXiv:1703.09312, 0
9
Learning traffic behaviors by extracting vehicle trajectories from online video streams
X Ren, D Wang, M Laskey, K Goldberg
2018 IEEE 14th International Conference on Automation Science and …, 2018
82018
Learning robust bed making using deep imitation learning with dart
M Laskey, C Powers, R Joshi, A Poursohi, K Goldberg
arXiv preprint arXiv:1711.02525, 2017
62017
A dynamic regret analysis and adaptive regularization algorithm for on-policy robot imitation learning
JN Lee, M Laskey, AK Tanwani, A Aswani, K Goldberg
International Workshop on the Algorithmic Foundations of Robotics, 212-227, 2018
52018
Generalizing robot imitation learning with invariant hidden semi-markov models
AK Tanwani, J Lee, B Thananjeyan, M Laskey, S Krishnan, R Fox, ...
International Workshop on the Algorithmic Foundations of Robotics, 196-211, 2018
42018
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
32017
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data
P Sundaresan, J Grannen, B Thananjeyan, A Balakrishna, M Laskey, ...
arXiv preprint arXiv:2003.01835, 2020
22020
Fluids: A first-order local urban intersection driving simulator
H Zhao, A Cui, SA Cullen, B Paden, M Laskey, K Goldberg
CASE., 2018
22018
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Articles 1–20