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06/14/2023
Online Learning for Obstacle Avoidance
We approach the fundamental problem of obstacle avoidance for robotic sy...
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04/26/2023
Fundamental Tradeoffs in Learning with Prior Information
We seek to understand fundamental tradeoffs between the accuracy of prio...
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02/09/2023
AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer
Simulation parameter settings such as contact models and object geometry...
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11/10/2022
Switching Attention in Time-Varying Environments via Bayesian Inference of Abstractions
Motivated by the goal of endowing robots with a means for focusing atten...
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10/12/2022
FlowDrone: Wind Estimation and Gust Rejection on UAVs Using Fast-Response Hot-Wire Flow Sensors
Unmanned aerial vehicles (UAVs) are finding use in applications that pla...
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06/27/2022
Leveraging Language for Accelerated Learning of Tool Manipulation
Robust and generalized tool manipulation requires an understanding of th...
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02/20/2022
Towards a Framework for Comparing the Complexity of Robotic Tasks
We are motivated by the problem of comparing the complexity of one robot...
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02/11/2022
Failure Prediction with Statistical Guarantees for Vision-Based Robot Control
We are motivated by the problem of performing failure prediction for saf...
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01/31/2022
Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning
Our goal is to develop theory and algorithms for establishing fundamenta...
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01/20/2022
Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees
Safety is a critical component of autonomous systems and remains a chall...
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11/16/2021
Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data
We are motivated by the problem of learning policies for robotic systems...
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11/16/2021
Learning Provably Robust Motion Planners Using Funnel Libraries
This paper presents an approach for learning motion planners that are ac...
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09/17/2021
Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy
The rapid development of affordable and compact high-fidelity sensors (e...
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07/13/2021
Distributionally Robust Policy Learning via Adversarial Environment Generation
Our goal is to train control policies that generalize well to unseen env...
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06/25/2021
Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning
Our goal is to perform out-of-distribution (OOD) detection, i.e., to det...
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02/26/2021
A Regret Minimization Approach to Iterative Learning Control
We consider the setting of iterative learning control, or model-based po...
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02/19/2021
Deluca – A Differentiable Control Library: Environments, Methods, and Benchmarking
We present an open-source library of natively differentiable physics and...
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02/12/2021
PAC-BUS: Meta-Learning Bounds via PAC-Bayes and Uniform Stability
We are motivated by the problem of providing strong generalization guara...
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12/12/2020
Generating Adversarial Disturbances for Controller Verification
We consider the problem of generating maximally adversarial disturbances...
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10/24/2020
LagNetViP: A Lagrangian Neural Network for Video Prediction
The dominant paradigms for video prediction rely on opaque transition mo...
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08/17/2020
Learning to Actively Reduce Memory Requirements for Robot Control Tasks
Robots equipped with rich sensing modalities (e.g., RGB-D cameras) perfo...
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08/05/2020
Generalization Guarantees for Multi-Modal Imitation Learning
Control policies from imitation learning can often fail to generalize to...
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07/16/2020
CoNES: Convex Natural Evolutionary Strategies
We present a novel algorithm – convex natural evolutionary strategies (C...
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06/01/2020
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
A fundamental challenge in reinforcement learning is to learn policies t...
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02/28/2020
Probably Approximately Correct Vision-Based Planning using Motion Primitives
This paper presents a deep reinforcement learning approach for synthesiz...
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02/04/2020
Learning Task-Driven Control Policies via Information Bottlenecks
This paper presents a reinforcement learning approach to synthesizing ta...
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08/14/2019
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics
Historically, scalability has been a major challenge to the successful a...
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09/20/2018
Task-Driven Estimation and Control via Information Bottlenecks
Our goal is to develop a principled and general algorithmic framework fo...
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06/11/2018
PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments
Our goal is to synthesize controllers for robots that provably generaliz...
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11/28/2017
Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods
The literature on Inverse Reinforcement Learning (IRL) typically assumes...
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10/30/2017
How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics
Endowing robots with the capability of assessing risk and making risk-aw...
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10/09/2017
Response to "Counterexample to global convergence of DSOS and SDSOS hierarchies"
In a recent note [8], the author provides a counterexample to the global...
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06/08/2017
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization
In recent years, optimization theory has been greatly impacted by the ad...
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01/15/2016