43 citations · 184 across the 40 of their papers we have counts for
9 papers · 1 filter
Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy
Vincent Pacelli, Anirudha Majumdar
The rapid development of affordable and compact high-fidelity sensors (e.g., cameras and LIDAR) allows robots to construct detailed estimates of their states and environments. Howe…
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics
Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi
Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this pa…
Task-Driven Estimation and Control via Information Bottlenecks
Vincent Pacelli, Anirudha Majumdar
Our goal is to develop a principled and general algorithmic framework for task-driven estimation and control for robotic systems. State-of-the-art approaches for controlling roboti…
Response to "Counterexample to global convergence of DSOS and SDSOS hierarchies"
Amir Ali Ahmadi, Anirudha Majumdar
In a recent note [8], the author provides a counterexample to the global convergence of what his work refers to as "the DSOS and SDSOS hierarchies" for polynomial optimization prob…
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization
Amir Ali Ahmadi, Anirudha Majumdar
In recent years, optimization theory has been greatly impacted by the advent of sum of squares (SOS) optimization. The reliance of this technique on large-scale semidefinite progra…
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms
Sumeet Singh, Yin-Lam Chow, Anirudha Majumdar +1
In this paper we present a framework for risk-sensitive model predictive control (MPC) of linear systems affected by stochastic multiplicative uncertainty. Our key innovation is to…
A Framework for Time-Consistent, Risk-Averse Model Predictive Control: Theory and Algorithms
Yin-Lam Chow, Marco Pavone
In this paper we present a framework for risk-averse model predictive control (MPC) of linear systems affected by multiplicative uncertainty. Our key innovation is to consider time…
Some Applications of Polynomial Optimization in Operations Research and Real-Time Decision Making
Amir Ali Ahmadi, Anirudha Majumdar
We demonstrate applications of algebraic techniques that optimize and certify polynomial inequalities to problems of interest in the operations research and transportation engineer…
Complexity of Ten Decision Problems in Continuous Time Dynamical Systems
Amir Ali Ahmadi, Anirudha Majumdar, Russ Tedrake
We show that for continuous time dynamical systems described by polynomial differential equations of modest degree (typically equal to three), the following decision problems which…