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07/14/2023
Linking vision and motion for self-supervised object-centric perception
Object-centric representations enable autonomous driving algorithms to r...
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01/04/2023
Cost Inference for Feedback Dynamic Games from Noisy Partial State Observations and Incomplete Trajectories
In multi-agent dynamic games, the Nash equilibrium state trajectory of e...
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12/01/2022
Multi-Task Imitation Learning for Linear Dynamical Systems
We study representation learning for efficient imitation learning over l...
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06/21/2022
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control
Learned models and policies can generalize effectively when evaluated wi...
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01/18/2022
Inducing Structure in Reward Learning by Learning Features
Reward learning enables robots to learn adaptable behaviors from human i...
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11/27/2021
Learning from learning machines: a new generation of AI technology to meet the needs of science
We outline emerging opportunities and challenges to enhance the utility ...
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09/22/2021
Incorporating Data Uncertainty in Object Tracking Algorithms
Methodologies for incorporating the uncertainties characteristic of data...
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09/15/2021
Multi-Task Learning with Sequence-Conditioned Transporter Networks
Enabling robots to solve multiple manipulation tasks has a wide range of...
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01/08/2021
The Computation of Approximate Generalized Feedback Nash Equilibria
We present the concept of a Generalized Feedback Nash Equilibrium (GFNE)...
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11/11/2020
Multi-Hypothesis Interactions in Game-Theoretic Motion Planning
We present a novel method for handling uncertainty about the intentions ...
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11/11/2020
Testing for Typicality with Respect to an Ensemble of Learned Distributions
Methods of performing anomaly detection on high-dimensional data sets ar...
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11/04/2020
DeepReach: A Deep Learning Approach to High-Dimensional Reachability
Hamilton-Jacobi (HJ) reachability analysis is an important formal verifi...
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10/26/2020
Expert Selection in High-Dimensional Markov Decision Processes
In this work we present a multi-armed bandit framework for online expert...
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06/23/2020
Feature Expansive Reward Learning: Rethinking Human Input
In collaborative human-robot scenarios, when a person is not satisfied w...
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03/20/2020
Visual Navigation Among Humans with Optimal Control as a Supervisor
Real world navigation requires robots to operate in unfamiliar, dynamic ...
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12/20/2019
Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
In Bansal et al. (2019), a novel visual navigation framework that combin...
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11/16/2019
Design of the First Insect-scale Spinning-wing Robot
Here we present the design of an insect-scale microrobot that generates ...
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08/09/2019
New Wing Stroke and Wing Pitch Approaches for Milligram-scale Aerial Devices
Here we report the construction of the simplest transmission mechanism e...
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08/09/2019
Design of the first sub-milligram flapping wing aerial vehicle
Here we report the first sub-milligram flapping wing vehicle which is ab...
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08/08/2019
An Insect-scale Self-sufficient Rolling Microrobot
We design an insect-sized rolling microrobot driven by continuously rota...
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08/08/2019
An Insect-scale Untethered Laser-powered Jumping Microrobot
We present the design of an insect-sized jumping microrobot measuring 17...
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03/06/2019
Combining Optimal Control and Learning for Visual Navigation in Novel Environments
Model-based control is a popular paradigm for robot navigation because i...
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02/20/2019
Regression-based Inverter Control for Decentralized Optimal Power Flow and Voltage Regulation
Electronic power inverters are capable of quickly delivering reactive po...
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02/19/2019
Fast Neural Network Verification via Shadow Prices
To use neural networks in safety-critical settings it is paramount to pr...
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09/27/2018
A Successive-Elimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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09/17/2018
The Parallelization of Riccati Recursion
A method is presented for parallelizing the computation of solutions to ...
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06/15/2018
Customized Local Differential Privacy for Multi-Agent Distributed Optimization
Real-time data-driven optimization and control problems over networks ma...
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06/14/2018
Data-Driven Decentralized Optimal Power Flow
The implementation of optimal power flow (OPF) methods to perform voltag...
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10/24/2017
A Sequential Approximation Framework for Coded Distributed Optimization
Building on the previous work of Lee et al. and Ferdinand et al. on code...
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09/10/2017
MBMF: Model-Based Priors for Model-Free Reinforcement Learning
Reinforcement Learning is divided in two main paradigms: model-free and ...
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07/20/2017