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ORCIDAnirudha Majumdar
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- affiliation: Princeton University, Mechanical and Aerospace Engineering, USA
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2020 – today
- 2024
[c40]Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime F. Fisac:
Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees (Abstract Reprint). AAAI 2024: 22699- [c39]Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh:
Physically Grounded Vision-Language Models for Robotic Manipulation. ICRA 2024: 12462-12469 - [i51]Eric Lepowsky, David Snyder, Alexander Glaser, Anirudha Majumdar:
Privacy-Preserving Map-Free Exploration for Confirming the Absence of a Radioactive Source. CoRR abs/2402.17130 (2024) - [i50]Anushri Dixit, Zhiting Mei, Meghan Booker, Mariko Storey-Matsutani, Allen Z. Ren, Anirudha Majumdar:
Perceive With Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception. CoRR abs/2403.08185 (2024) - [i49]Allen Z. Ren, Jaden Clark, Anushri Dixit, Masha Itkina, Anirudha Majumdar, Dorsa Sadigh:
Explore until Confident: Efficient Exploration for Embodied Question Answering. CoRR abs/2403.15941 (2024) - [i48]Justin Lidard, Hang Pham, Ariel Bachman, Bryan Boateng, Anirudha Majumdar:
Risk-Calibrated Human-Robot Interaction via Set-Valued Intent Prediction. CoRR abs/2403.15959 (2024) - [i47]Allen Z. Ren, Justin Lidard, Lars Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz:
Diffusion Policy Policy Optimization. CoRR abs/2409.00588 (2024) - [i46]Y. Isabel Liu, Windsor Nguyen, Yagiz Devre, Evan Dogariu, Anirudha Majumdar, Elad Hazan:
Flash STU: Fast Spectral Transform Units. CoRR abs/2409.10489 (2024) - [i45]Asher Hancock, Allen Z. Ren, Anirudha Majumdar:
Run-time Observation Interventions Make Vision-Language-Action Models More Visually Robust. CoRR abs/2410.01971 (2024) - 2023
- [j12]Kai-Chieh Hsu
, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime F. Fisac:
Sim-to-Lab-to-Real: Safe reinforcement learning with shielding and generalization guarantees. Artif. Intell. 314: 103811 (2023) - [j11]Sumeet Singh, Benoit Landry, Anirudha Majumdar, Jean-Jacques E. Slotine, Marco Pavone:
Robust feedback motion planning via contraction theory. Int. J. Robotics Res. 42(9): 655-688 (2023) - [j10]Anirudha Majumdar, Zhiting Mei, Vincent Pacelli:
Fundamental limits for sensor-based robot control. Int. J. Robotics Res. 42(12): 1051-1069 (2023) - [c38]Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar:
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners. CoRL 2023: 661-682 - [c37]David Snyder, Meghan Booker, Nathaniel Simon, Wenhan Xia, Daniel Suo, Elad Hazan, Anirudha Majumdar:
Online Learning for Obstacle Avoidance. CoRL 2023: 2926-2954 - [c36]Allen Z. Ren, Hongkai Dai, Benjamin Burchfiel, Anirudha Majumdar:
AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer. CoRL 2023: 3434-3452 - [c35]Anirudha Majumdar:
Fundamental Tradeoffs in Learning with Prior Information. ICML 2023: 23558-23573 - [c34]Nathaniel Simon, Allen Z. Ren, Alexander Piqué, David Snyder, Daphne Barretto, Marcus Hultmark, Anirudha Majumdar:
FlowDrone: Wind Estimation and Gust Rejection on UAVs Using Fast-Response Hot-Wire Flow Sensors. ICRA 2023: 5393-5399 - [c33]Meghan Booker, Anirudha Majumdar:
Switching Attention in Time-Varying Environments via Bayesian Inference of Abstractions. ICRA 2023: 10174-10180 - [c32]Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone, Anirudha Majumdar:
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction. NeurIPS 2023 - [i44]Allen Z. Ren, Hongkai Dai, Benjamin Burchfiel, Anirudha Majumdar:
AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer. CoRR abs/2302.04903 (2023) - [i43]Anirudha Majumdar:
Fundamental Tradeoffs in Learning with Prior Information. CoRR abs/2304.13479 (2023) - [i42]David Snyder, Meghan Booker, Nathaniel Simon, Wenhan Xia, Daniel Suo, Elad Hazan, Anirudha Majumdar:
Online Learning for Obstacle Avoidance. CoRR abs/2306.08776 (2023) - [i41]Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar:
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners. CoRR abs/2307.01928 (2023) - [i40]Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh:
Physically Grounded Vision-Language Models for Robotic Manipulation. CoRR abs/2309.02561 (2023) - [i39]Nathaniel Simon, Anirudha Majumdar:
MonoNav: MAV Navigation via Monocular Depth Estimation and Reconstruction. CoRR abs/2311.14100 (2023) - [i38]Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone, Anirudha Majumdar:
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction. CoRR abs/2312.04658 (2023) - [i37]Roya Firoozi, Johnathan Tucker, Stephen Tian, Anirudha Majumdar, Jiankai Sun, Weiyu Liu, Yuke Zhu, Shuran Song, Ashish Kapoor, Karol Hausman, Brian Ichter, Danny Driess, Jiajun Wu, Cewu Lu, Mac Schwager:
Foundation Models in Robotics: Applications, Challenges, and the Future. CoRR abs/2312.07843 (2023) - 2022
- [j9]Allen Z. Ren, Anirudha Majumdar:
Distributionally Robust Policy Learning via Adversarial Environment Generation. IEEE Robotics Autom. Lett. 7(2): 1379-1386 (2022) - [c31]Allen Z. Ren, Bharat Govil, Tsung-Yen Yang, Karthik R. Narasimhan, Anirudha Majumdar:
Leveraging Language for Accelerated Learning of Tool Manipulation. CoRL 2022: 1531-1541 - [c30]Vincent Pacelli, Anirudha Majumdar:
Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy. ICRA 2022: 3467-3474 - [c29]Abhinav Agarwal, Sushant Veer, Allen Z. Ren, Anirudha Majumdar:
Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data. ICRA 2022: 4414-4421 - [c28]Alec Farid, David Snyder, Allen Z. Ren, Anirudha Majumdar:
Failure Prediction with Statistical Guarantees for Vision-Based Robot Control. Robotics: Science and Systems 2022 - [c27]Anirudha Majumdar, Vincent Pacelli:
Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning. Robotics: Science and Systems 2022 - [c26]Michelle Ho, Alec Farid, Anirudha Majumdar:
Towards a Framework for Comparing the Complexity of Robotic Tasks. WAFR 2022: 273-293 - [i36]Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime F. Fisac:
Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees. CoRR abs/2201.08355 (2022) - [i35]Anirudha Majumdar, Vincent Pacelli:
Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning. CoRR abs/2202.00129 (2022) - [i34]Alec Farid, David Snyder, Allen Z. Ren, Anirudha Majumdar:
Failure Prediction with Statistical Guarantees for Vision-Based Robot Control. CoRR abs/2202.05894 (2022) - [i33]Michelle Ho, Alec Farid, Anirudha Majumdar:
Comparing the Complexity of Robotic Tasks. CoRR abs/2202.09892 (2022) - [i32]Allen Z. Ren, Bharat Govil, Tsung-Yen Yang, Karthik Narasimhan, Anirudha Majumdar:
Leveraging Language for Accelerated Learning of Tool Manipulation. CoRR abs/2206.13074 (2022) - [i31]Nathaniel Simon, Allen Z. Ren, Alexander Piqué, David Snyder, Daphne Barretto, Marcus Hultmark, Anirudha Majumdar:
FlowDrone: Wind Estimation and Gust Rejection on UAVs Using Fast-Response Hot-Wire Flow Sensors. CoRR abs/2210.05857 (2022) - [i30]Meghan Booker, Anirudha Majumdar:
Switching Attention in Time-Varying Environments via Bayesian Inference of Abstractions. CoRR abs/2211.05865 (2022) - 2021
- [j8]Anirudha Majumdar, Alec Farid, Anoopkumar Sonar:
PAC-Bayes control: learning policies that provably generalize to novel environments. Int. J. Robotics Res. 40(2-3) (2021) - [c25]Alec Farid, Sushant Veer, Anirudha Majumdar:
Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning. CoRL 2021: 970-980 - [c24]Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh:
A Regret Minimization Approach to Iterative Learning Control. ICML 2021: 100-109 - [c23]Anoopkumar Sonar, Vincent Pacelli, Anirudha Majumdar:
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning. L4DC 2021: 21-33 - [c22]Meghan Booker, Anirudha Majumdar:
Learning to Actively Reduce Memory Requirements for Robot Control Tasks. L4DC 2021: 125-137 - [c21]Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan:
Generating Adversarial Disturbances for Controller Verification. L4DC 2021: 1192-1204 - [c20]Alec Farid, Anirudha Majumdar:
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability. NeurIPS 2021: 2173-2186 - [i29]Alec Farid, Anirudha Majumdar:
PAC-BUS: Meta-Learning Bounds via PAC-Bayes and Uniform Stability. CoRR abs/2102.06589 (2021) - [i28]Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan:
Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR abs/2102.09968 (2021) - [i27]Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh:
A Regret Minimization Approach to Iterative Learning Control. CoRR abs/2102.13478 (2021) - [i26]Alec Farid, Sushant Veer, Anirudha Majumdar:
Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning. CoRR abs/2106.13703 (2021) - [i25]Allen Z. Ren, Anirudha Majumdar:
Distributionally Robust Policy Learning via Adversarial Environment Generation. CoRR abs/2107.06353 (2021) - [i24]Vincent Pacelli, Anirudha Majumdar:
Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy. CoRR abs/2109.08262 (2021) - [i23]Ali Ekin Gurgen, Anirudha Majumdar, Sushant Veer:
Learning Provably Robust Motion Planners Using Funnel Libraries. CoRR abs/2111.08733 (2021) - [i22]Abhinav Agarwal, Sushant Veer, Allen Z. Ren, Anirudha Majumdar:
Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data. CoRR abs/2111.08761 (2021) - 2020
- [j7]Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi:
Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics. Annu. Rev. Control. Robotics Auton. Syst. 3: 331-360 (2020) - [c19]Sushant Veer, Anirudha Majumdar:
Probably Approximately Correct Vision-Based Planning using Motion Primitives. CoRL 2020: 1001-1014 - [c18]Allen Z. Ren, Sushant Veer, Anirudha Majumdar:
Generalization Guarantees for Imitation Learning. CoRL 2020: 1426-1442 - [c17]Vincent Pacelli, Anirudha Majumdar:
Learning Task-Driven Control Policies via Information Bottlenecks. Robotics: Science and Systems 2020 - [i21]Vincent Pacelli, Anirudha Majumdar:
Learning Task-Driven Control Policies via Information Bottlenecks. CoRR abs/2002.01428 (2020) - [i20]Sushant Veer, Anirudha Majumdar:
Probably Approximately Correct Vision-Based Planning using Motion Primitives. CoRR abs/2002.12852 (2020) - [i19]Anoopkumar Sonar, Vincent Pacelli, Anirudha Majumdar:
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning. CoRR abs/2006.01096 (2020) - [i18]Sushant Veer, Anirudha Majumdar:
CoNES: Convex Natural Evolutionary Strategies. CoRR abs/2007.08601 (2020) - [i17]Allen Z. Ren, Sushant Veer, Anirudha Majumdar:
Generalization Guarantees for Multi-Modal Imitation Learning. CoRR abs/2008.01913 (2020) - [i16]Meghan Booker, Anirudha Majumdar:
Learning to Actively Reduce Memory Requirements for Robot Control Tasks. CoRR abs/2008.07451 (2020) - [i15]Christine Allen-Blanchette, Sushant Veer, Anirudha Majumdar, Naomi Ehrich Leonard:
LagNetViP: A Lagrangian Neural Network for Video Prediction. CoRR abs/2010.12932 (2020) - [i14]Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan:
Generating Adversarial Disturbances for Controller Verification. CoRR abs/2012.06695 (2020)
2010 – 2019
- 2019
- [j6]Amir Ali Ahmadi, Anirudha Majumdar:
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization. SIAM J. Appl. Algebra Geom. 3(2): 193-230 (2019) - [j5]Sumeet Singh, Yinlam Chow, Anirudha Majumdar, Marco Pavone:
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms. IEEE Trans. Autom. Control. 64(7): 2905-2912 (2019) - [c16]Vincent Pacelli, Anirudha Majumdar:
Task-Driven Estimation and Control via Information Bottlenecks. ICRA 2019: 2061-2067 - [i13]Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi:
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics. CoRR abs/1908.05209 (2019) - 2018
- [j4]Sumeet Singh, Jonathan Lacotte, Anirudha Majumdar, Marco Pavone:
Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods. Int. J. Robotics Res. 37(13-14) (2018) - [c15]Anirudha Majumdar, Maxwell Goldstein:
PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments. CoRL 2018: 293-305 - [i12]Anirudha Majumdar, Maxwell Goldstein:
PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments. CoRR abs/1806.04225 (2018) - [i11]Vincent Pacelli, Anirudha Majumdar:
Task-Driven Estimation and Control via Information Bottlenecks. CoRR abs/1809.07874 (2018) - 2017
- [j3]Anirudha Majumdar, Russ Tedrake:
Funnel libraries for real-time robust feedback motion planning. Int. J. Robotics Res. 36(8): 947-982 (2017) - [c14]Sumeet Singh, Anirudha Majumdar, Jean-Jacques E. Slotine, Marco Pavone:
Robust online motion planning via contraction theory and convex optimization. ICRA 2017: 5883-5890 - [c13]Anirudha Majumdar, Marco Pavone:
How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics. ISRR 2017: 75-84 - [c12]Anirudha Majumdar, Sumeet Singh, Ajay Mandlekar, Marco Pavone:
Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models. Robotics: Science and Systems 2017 - [i10]Yin-Lam Chow, Sumeet Singh, Anirudha Majumdar, Marco Pavone:
A Framework for Time-Consistent, Risk-Averse Model Predictive Control: Theory and Algorithms. CoRR abs/1703.01029 (2017) - [i9]Amir Ali Ahmadi, Anirudha Majumdar:
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization. CoRR abs/1706.02586 (2017) - [i8]Amir Ali Ahmadi, Anirudha Majumdar:
Response to "Counterexample to global convergence of DSOS and SDSOS hierarchies". CoRR abs/1710.02901 (2017) - [i7]Anirudha Majumdar, Marco Pavone:
How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics. CoRR abs/1710.11040 (2017) - [i6]Sumeet Singh, Jonathan Lacotte, Anirudha Majumdar, Marco Pavone:
Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods. CoRR abs/1711.10055 (2017) - 2016
- [b1]Anirudha Majumdar:
Funnel libraries for real-time robust feedback motion planning. Massachusetts Institute of Technology, Cambridge, USA, 2016 - [j2]Amir Ali Ahmadi, Anirudha Majumdar:
Some applications of polynomial optimization in operations research and real-time decision making. Optim. Lett. 10(4): 709-729 (2016) - [i5]Anirudha Majumdar, Russ Tedrake:
Funnel Libraries for Real-Time Robust Feedback Motion Planning. CoRR abs/1601.04037 (2016) - 2015
- [c11]Hongkai Dai, Anirudha Majumdar, Russ Tedrake:
Synthesis and Optimization of Force Closure Grasps via Sequential Semidefinite Programming. ISRR (1) 2015: 285-305 - [i4]Amir Ali Ahmadi, Anirudha Majumdar:
Some Applications of Polynomial Optimization in Operations Research and Real-Time Decision Making. CoRR abs/1504.06002 (2015) - 2014
- [j1]Anirudha Majumdar, Ram Vasudevan, Mark M. Tobenkin, Russ Tedrake:
Convex optimization of nonlinear feedback controllers via occupation measures. Int. J. Robotics Res. 33(9): 1209-1230 (2014) - [c10]Anirudha Majumdar, Amir Ali Ahmadi, Russ Tedrake:
Control and verification of high-dimensional systems with DSOS and SDSOS programming. CDC 2014: 394-401 - [c9]Amir Ali Ahmadi, Anirudha Majumdar:
DSOS and SDSOS optimization: LP and SOCP-based alternatives to sum of squares optimization. CISS 2014: 1-5 - [c8]Andrew J. Barry, Tim Jenks, Anirudha Majumdar, Huai-Ti Lin, Ivo G. Ros, Andrew A. Biewener, Russ Tedrake:
Flying between obstacles with an autonomous knife-edge maneuver. ICRA 2014: 2559 - 2013
- [c7]Amir Ali Ahmadi, Anirudha Majumdar, Russ Tedrake:
Complexity of ten decision problems in continuous time dynamical systems. ACC 2013: 6376-6381 - [c6]Anirudha Majumdar, Amir Ali Ahmadi, Russ Tedrake:
Control design along trajectories with sums of squares programming. ICRA 2013: 4054-4061 - [c5]Anirudha Majumdar, Ram Vasudevan, Mark M. Tobenkin, Russ Tedrake:
Convex Optimization of Nonlinear Feedback Controllers via Occupation Measures. Robotics: Science and Systems 2013 - [i3]Anirudha Majumdar, Ram Vasudevan, Mark M. Tobenkin, Russ Tedrake:
Technical Report: Convex Optimization of Nonlinear Feedback Controllers via Occupation Measures. CoRR abs/1305.7484 (2013) - 2012
- [c4]Anirudha Majumdar, Mark M. Tobenkin, Russ Tedrake:
Algebraic verification for parameterized motion planning libraries. ACC 2012: 250-257 - [c3]Andrew J. Barry, Anirudha Majumdar, Russ Tedrake:
Safety verification of reactive controllers for UAV flight in cluttered environments using barrier certificates. ICRA 2012: 484-490 - [c2]Anirudha Majumdar, Russ Tedrake:
Robust Online Motion Planning with Regions of Finite Time Invariance. WAFR 2012: 543-558 - [i2]Anirudha Majumdar, Amir Ali Ahmadi, Russ Tedrake:
Control Design along Trajectories with Sums of Squares Programming. CoRR abs/1210.0888 (2012) - [i1]Amir Ali Ahmadi, Anirudha Majumdar, Russ Tedrake:
Complexity of Ten Decision Problems in Continuous Time Dynamical Systems. CoRR abs/1210.7420 (2012) - 2010
- [c1]Haldun Komsuoglu, Anirudha Majumdar, Yasemin Ozkan Aydin, Daniel E. Koditschek:
Characterization of Dynamic Behaviors in a Hexapod Robot. ISER 2010: 667-684
Coauthor Index
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