| Formally correct composition of coordinated behaviors using control barrier certificates A Li, L Wang, P Pierpaoli, M Egerstedt 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 78 | 2018 |
| Euclideanizing flows: Diffeomorphic reduction for learning stable dynamical systems MA Rana, A Li, D Fox, B Boots, F Ramos, N Ratliff Learning for Dynamics and Control, 630-639, 2020 | 68 | 2020 |
| Geometric fabrics: Generalizing classical mechanics to capture the physics of behavior K Van Wyk, M Xie, A Li, MA Rana, B Babich, B Peele, Q Wan, I Akinola, ... IEEE Robotics and Automation Letters 7 (2), 3202-3209, 2022 | 46 | 2022 |
| TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation X Meng, N Hatch, A Lambert, A Li, N Wagener, M Schmittle, JH Lee, ... arXiv preprint arXiv:2303.15771, 2023 | 45 | 2023 |
| Learning reactive motion policies in multiple task spaces from human demonstrations MA Rana, A Li, H Ravichandar, M Mukadam, S Chernova, D Fox, B Boots, ... Conference on Robot Learning, 1457-1468, 2020 | 33 | 2020 |
| Composable energy policies for reactive motion generation and reinforcement learning J Urain, A Li, P Liu, C D’Eramo, J Peters The International Journal of Robotics Research 42 (10), 827-858, 2023 | 30 | 2023 |
| Generalized nonlinear and finsler geometry for robotics ND Ratliff, K Van Wyk, M Xie, A Li, MA Rana 2021 IEEE International Conference on Robotics and Automation (ICRA), 10206 …, 2021 | 29 | 2021 |
| Survival instinct in offline reinforcement learning A Li, D Misra, A Kolobov, CA Cheng Advances in neural information processing systems 36, 2024 | 21 | 2024 |
| Geometric Fabrics for the Acceleration-based Design of Robotic Motion M Xie, K Van Wyk, A Li, MA Rana, Q Wan, D Fox, B Boots, N Ratliff arXiv preprint arXiv:2010.14750, 2020 | 20 | 2020 |
| Optimization fabrics ND Ratliff, K Van Wyk, M Xie, A Li, MA Rana arXiv preprint arXiv:2008.02399, 2020 | 20 | 2020 |
| Mahalo: Unifying offline reinforcement learning and imitation learning from observations A Li, B Boots, CA Cheng International Conference on Machine Learning, 19360-19384, 2023 | 19 | 2023 |
| RMP2: A Structured Composable Policy Class for Robot Learning A Li, CA Cheng, MA Rana, M Xie, K Van Wyk, N Ratliff, B Boots arXiv preprint arXiv:2103.05922, 2021 | 19 | 2021 |
| A Sequential Composition Framework for Coordinating Multirobot Behaviors P Pierpaoli, A Li, M Srinivasan, X Cai, S Coogan, M Egerstedt IEEE Transactions on Robotics 37 (3), 864-876, 2020 | 17 | 2020 |
| Multi-Objective Policy Generation for Multi-Robot Systems Using Riemannian Motion Policies A Li, M Mukadam, M Egerstedt, B Boots arXiv preprint arXiv:1902.05177, 2019 | 17 | 2019 |
| Stable, concurrent controller composition for multi-objective robotic tasks A Li, CA Cheng, B Boots, M Egerstedt 2019 IEEE 58th Conference on Decision and Control (CDC), 1144-1151, 2019 | 14 | 2019 |
| Model Predictive Control for Aggressive Driving Over Uneven Terrain T Han, A Liu, A Li, A Spitzer, G Shi, B Boots arXiv preprint arXiv:2311.12284, 2023 | 13 | 2023 |
| Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees MA Rana, A Li, D Fox, S Chernova, B Boots, N Ratliff 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 8 | 2021 |
| Decentralized coordinated motion for a large team of robots preserving connectivity and avoiding collisions A Li, W Luo, S Nagavalli, K Sycara 2017 IEEE International Conference on Robotics and Automation (ICRA), 1505-1511, 2017 | 8 | 2017 |
| Inferring and Learning Multi-Robot Policies by Observing an Expert P Pierpaoli, H Ravichandar, N Waytowich, A Li, D Asher, M Egerstedt arXiv preprint arXiv:1909.07887, 2019 | 7 | 2019 |
| Imitation learning via simultaneous optimization of policies and auxiliary trajectories M Xie, A Li, K Van Wyk, F Dellaert, B Boots, N Ratliff arXiv preprint arXiv:2105.03019, 2021 | 3 | 2021 |
Byron BootsAssociate Professor, University of Washington確認したメール アドレス: cs.washington.edu