
Koopman NMPC: Koopmanbased Learning and Nonlinear Model Predictive Control of Controlaffine Systems
Koopmanbased learning methods can potentially be practical and powerful...
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RiskAverse Stochastic Shortest Path Planning
We consider the stochastic shortest path planning problem in MDPs, i.e.,...
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Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty
When autonomous robots interact with humans, such as during autonomous d...
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Learning Invariant Representation of Tasks for Robust Surgical State Estimation
Surgical state estimators in robotassisted surgery (RAS)  especially t...
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RiskSensitive Motion Planning using Entropic ValueatRisk
We consider the problem of risksensitive motion planning in the presenc...
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ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
Characterizing what types of exoskeleton gaits are comfortable for users...
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daVinciNet: Joint Prediction of Motion and Surgical State in RobotAssisted Surgery
This paper presents a technique to concurrently and jointly predict the ...
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Safe MultiAgent Interaction through Robust Control Barrier Functions with Learned Uncertainties
Robots operating in real world settings must navigate and maintain safet...
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Barrier Functions for MultiagentPOMDPs with DTL Specifications
Multiagent partially observable Markov decision processes (MPOMDPs) pro...
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Human PreferenceBased Learning for Highdimensional Optimization of Exoskeleton Walking Gaits
Understanding users' gait preferences of a lowerbody exoskeleton requir...
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Temporal Segmentation of Surgical Subtasks through Deep Learning with Multiple Data Sources
Many tasks in robotassisted surgeries (RAS) can be represented by finit...
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Stochastic Finite State Control of POMDPs with LTL Specifications
Partially observable Markov decision processes (POMDPs) provide a modeli...
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Optimal Motion Planning for MultiModal Hybrid Locomotion
Hybrid locomotion, which combines multiple modalities of locomotion with...
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Dueling Posterior Sampling for PreferenceBased Reinforcement Learning
In preferencebased reinforcement learning (RL), an agent interacts with...
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Control Regularization for Reduced Variance Reinforcement Learning
Dealing with high variance is a significant challenge in modelfree rein...
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EndtoEnd Safe Reinforcement Learning through Barrier Functions for SafetyCritical Continuous Control Tasks
Reinforcement Learning (RL) algorithms have found limited success beyond...
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Safe Policy Synthesis in MultiAgent POMDPs via DiscreteTime Barrier Functions
A multiagent partially observable Markov decision process (MPOMDP) is a...
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Stagewise Safe Bayesian Optimization with Gaussian Processes
Enforcing safety is a key aspect of many problems pertaining to sequenti...
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Quantifying Performance of Bipedal Standing with Multichannel EMG
Spinal cord stimulation has enabled humans with motor complete spinal co...
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Meta Inverse Reinforcement Learning via Maximum Reward Sharing for Human Motion Analysis
This work handles the inverse reinforcement learning (IRL) problem where...
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Clinical Patient Tracking in the Presence of Transient and Permanent Occlusions via Geodesic Feature
This paper develops a method to use RGBD cameras to track the motions o...
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Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation
This paper proposes a new method for rigid body pose estimation based on...
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Joel W. Burdick
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