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Anirudha Majumdar
Anirudha Majumdar
Associate Professor, Princeton University & Visiting Research Scientist, Google DeepMind
Bestätigte E-Mail-Adresse bei princeton.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Funnel libraries for real-time robust feedback motion planning
A Majumdar, R Tedrake
International Journal of Robotics Research 36 (8), 947-982, 2017
4692017
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
2772019
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
2682019
Robust Online Motion Planning via Contraction Theory and Convex Optimization
S Singh, A Majumdar, JJ Slotine, M Pavone
2302017
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
2252020
Control design along trajectories with sums of squares programming
A Majumdar, AA Ahmadi, R Tedrake
International Conference on Robotics and Automation (ICRA), 2013, 2013
1922013
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
1532014
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
1422014
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
1412023
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
1262020
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
1102013
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
Some applications of polynomial optimization in operations research and real-time decision making
AA Ahmadi, A Majumdar
Optimization Letters 10, 709-729, 2016
842016
Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models
A Majumdar, S Singh, A Mandlekar, M Pavone
Robotics: Science and Systems 16, 117, 2017
792017
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
702018
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
692023
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
622012
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
582024
Invariant policy optimization: Towards stronger generalization in reinforcement learning
A Sonar, V Pacelli, A Majumdar
Learning for Dynamics and Control, 21-33, 2021
552021
Synthesis and Optimization of Force Closure Grasps via Sequential Semidefinite Programming
H Dai, A Majumdar, R Tedrake
International Symposium on Robotics Research (ISRR), 2015
522015
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