Anirudha Majumdar

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Russ TedrakeMIT (EECS, MechE, Aero/Astro) and Toyota Research InstituteVerifierad e-postadress på mit.edu
Allen Z. RenPrinceton UniversityVerifierad e-postadress på princeton.edu
Marco PavoneStanford University and NVIDIAVerifierad e-postadress på stanford.edu
Sumeet SinghResearch Scientist, Google Brain RoboticsVerifierad e-postadress på google.com
Sushant VeerNVIDIAVerifierad e-postadress på nvidia.com
Alec FaridPh.D. Princeton University, ZooxVerifierad e-postadress på princeton.edu
Dorsa SadighStanford UniversityVerifierad e-postadress på cs.stanford.edu
Anushri DixitAssistant Professor, UCLAVerifierad e-postadress på ucla.edu
Brian IchterPhysical IntelligenceVerifierad e-postadress på physicalintelligence.company
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerifierad e-postadress på princeton.edu
Jean-Jacques SlotineMIT, Professor of Mechanical Engineering and Information Sciences, Professor of Brain SciencesVerifierad e-postadress på mit.edu
Fei XiaResearch Scientist, Google DeepMindVerifierad e-postadress på google.com
Nathaniel SimonPrinceton UniversityVerifierad e-postadress på princeton.edu
Ram VasudevanAssociate Professor of Robotics and Mechanical Engineering, University of MichiganVerifierad e-postadress på umich.edu
Hongkai DaiToyota Research InstituteVerifierad e-postadress på mit.edu
Mac SchwagerStanford UniversityVerifierad e-postadress på stanford.edu
Jiankai SunStanford UniversityVerifierad e-postadress på cs.stanford.edu
Anoopkumar S SonarRobotics PhD student, MITVerifierad e-postadress på mit.edu
Jaime Fernández FisacAssistant Professor of Electrical and Computer Engineering, Princeton UniversityVerifierad e-postadress på princeton.edu
Duy Phuong NguyenPhD Candidate at Electrical and Computer Engineering, Princeton UniversityVerifierad e-postadress på princeton.edu

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Anirudha Majumdar

Associate Professor, Princeton University & Visiting Research Scientist, Google DeepMind

Verifierad e-postadress på princeton.edu - Startsida

Robotics Machine Learning Motion Planning Control


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Funnel libraries for real-time robust feedback motion planning A Majumdar, R Tedrake International Journal of Robotics Research 36 (8), 947-982, 2017	489	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	288	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	279	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	233	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	195	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
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
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	142	2020
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	127	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	91	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	59	2021

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