| 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 | 1410 | 2017 |
| 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 | 449 | 2016 |
| Dart: Noise injection for robust imitation learning M Laskey, J Lee, R Fox, A Dragan, K Goldberg Conference on robot learning, 143-156, 2017 | 282 | 2017 |
| 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 | 145 | 2020 |
| 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: Selected Contributions of the …, 2015 | 109 | 2015 |
| 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 | 102 | 2019 |
| 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 | 100 | 2016 |
| 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 | 96 | 2014 |
| 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 | 95 | 2016 |
| 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 | 87 | 2017 |
| Centersnap: Single-shot multi-object 3d shape reconstruction and categorical 6d pose and size estimation MZ Irshad, T Kollar, M Laskey, K Stone, Z Kira 2022 International Conference on Robotics and Automation (ICRA), 10632-10640, 2022 | 73 | 2022 |
| Untangling dense knots by learning task-relevant keypoints J Grannen, P Sundaresan, B Thananjeyan, J Ichnowski, A Balakrishna, ... arXiv preprint arXiv:2011.04999, 2020 | 63 | 2020 |
| 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 | 63 | 2015 |
| Real2sim2real: Self-supervised learning of physical single-step dynamic actions for planar robot casting V Lim, H Huang, LY Chen, J Wang, J Ichnowski, D Seita, M Laskey, ... 2022 International Conference on Robotics and Automation (ICRA), 8282-8289, 2022 | 61 | 2022 |
| 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 | 37 | |
| Planar robot casting with real2sim2real self-supervised learning V Lim, H Huang, LY Chen, J Wang, J Ichnowski, D Seita, M Laskey, ... arXiv preprint arXiv:2111.04814, 2021 | 34 | 2021 |
| 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 | 34 | 2017 |
| Simnet: Enabling robust unknown object manipulation from pure synthetic data via stereo T Kollar, M Laskey, K Stone, B Thananjeyan, M Tjersland Conference on Robot Learning, 938-948, 2022 | 31 | 2022 |
| A mobile manipulation system for one-shot teaching of complex tasks in homes M Bajracharya, J Borders, D Helmick, T Kollar, M Laskey, J Leichty, J Ma, ... 2020 IEEE International Conference on Robotics and Automation (ICRA), 11039 …, 2020 | 31 | 2020 |
| Untangling dense non-planar knots by learning manipulation features and recovery policies P Sundaresan, J Grannen, B Thananjeyan, A Balakrishna, J Ichnowski, ... arXiv preprint arXiv:2107.08942, 2021 | 30 | 2021 |
