| Funnel libraries for real-time robust feedback motion planning A Majumdar, R Tedrake International Journal of Robotics Research 36 (8), 947-982, 2017 | 490 | 2017 |
| DSOS and SDSOS optimization: more tractable alternatives to sum of squares and semidefinite optimization AA Ahmadi, A Majumdar SIAM Journal on Applied Algebra and Geometry 3 (2), 193-230, 2019 | 289 | 2019 |
| DSOS and SDSOS optimization: more tractable alternatives to sum of squares and semidefinite optimization AA Ahmadi, A Majumdar SIAM Journal on Applied Algebra and Geometry 3 (2), 193-230, 2019 | 280 | 2019 |
| How should a robot assess risk? towards an axiomatic theory of risk in robotics A Majumdar, M Pavone Robotics Research: The 18th International Symposium ISRR, 75-84, 2020 | 239 | 2020 |
| Robust Online Motion Planning via Contraction Theory and Convex Optimization S Singh, A Majumdar, JJ Slotine, M Pavone | 232 | 2017 |
| Control design along trajectories with sums of squares programming A Majumdar, AA Ahmadi, R Tedrake International Conference on Robotics and Automation (ICRA), 2013, 2013 | 201 | 2013 |
| Robots that ask for help: Uncertainty alignment for large language model planners AZ Ren, A Dixit, A Bodrova, S Singh, S Tu, N Brown, P Xu, L Takayama, ... arXiv preprint arXiv:2307.01928, 2023 | 193 | 2023 |
| Convex Optimization of Nonlinear Feedback Controllers via Occupation Measures A Majumdar, R Vasudevan, MM Tobenkin, R Tedrake International Journal of Robotics Research (IJRR) 33 (9), 1209-1230, 2014 | 155 | 2014 |
| Recent scalability improvements for semidefinite programming with applications in machine learning, control, and robotics A Majumdar, G Hall, AA Ahmadi Annual Review of Control, Robotics, and Autonomous Systems 3 (1), 331-360, 2020 | 143 | 2020 |
| DSOS and SDSOS optimization: LP and SOCP-based alternatives to sum of squares optimization AA Ahmadi, A Majumdar 2014 48th annual conference on information sciences and systems (CISS), 1-5, 2014 | 143 | 2014 |
| Foundation models in robotics: Applications, challenges, and the future R Firoozi, J Tucker, S Tian, A Majumdar, J Sun, W Liu, Y Zhu, S Song, ... The International Journal of Robotics Research, 02783649241281508, 2023 | 126 | 2023 |
| Robust online motion planning with regions of finite time invariance A Majumdar, R Tedrake Algorithmic Foundations of Robotics X: Proceedings of the Tenth Workshop on …, 2013 | 111 | 2013 |
| Control and verification of high-dimensional systems with DSOS and SDSOS programming A Majumdar, AA Ahmadi, R Tedrake IEEE Conference on Decision and Control (CDC), 394-401, 2014 | 100* | 2014 |
| Physically grounded vision-language models for robotic manipulation J Gao, B Sarkar, F Xia, T Xiao, J Wu, B Ichter, A Majumdar, D Sadigh 2024 IEEE International Conference on Robotics and Automation (ICRA), 12462 …, 2024 | 90 | 2024 |
| Some applications of polynomial optimization in operations research and real-time decision making AA Ahmadi, A Majumdar Optimization Letters 10, 709-729, 2016 | 89 | 2016 |
| Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models A Majumdar, S Singh, A Mandlekar, M Pavone Robotics: Science and Systems 16, 117, 2017 | 85 | 2017 |
| A framework for time-consistent, risk-sensitive model predictive control: Theory and algorithms S Singh, Y Chow, A Majumdar, M Pavone IEEE Transactions on Automatic Control 64 (7), 2905-2912, 2018 | 73 | 2018 |
| Safety verification of reactive controllers for UAV flight in cluttered environments using barrier certificates AJ Barry, A Majumdar, R Tedrake 2012 IEEE International Conference on Robotics and Automation, 484-490, 2012 | 64 | 2012 |
| Invariant policy optimization: Towards stronger generalization in reinforcement learning A Sonar, V Pacelli, A Majumdar Learning for Dynamics and Control, 21-33, 2021 | 60 | 2021 |
| Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability A Farid, A Majumdar Advances in Neural Information Processing Systems (NeurIPS), 2021 | 58 | 2021 |
Russ TedrakeMIT (EECS, MechE, Aero/Astro) and Toyota Research Institutemit.edu의 이메일 확인됨