182 citations · 874 across the 39 of their papers we have counts for
5 papers · 1 filter
Factored Contextual Policy Search with Bayesian Optimization
Peter Karkus, Andras Kupcsik, David Hsu +1
Scarce data is a major challenge to scaling robot learning to truly complex tasks, as we need to generalize locally learned policies over different "contexts". Bayesian optimizatio…
DESPOT: Online POMDP Planning with Regularization
Nan Ye, Adhiraj Somani, David Hsu +1
The partially observable Markov decision process (POMDP) provides a principled general framework for planning under uncertainty, but solving POMDPs optimally is computationally int…
Configuration Lattices for Planar Contact Manipulation Under Uncertainty
Michael C. Koval, David Hsu, Nancy S. Pollard +1
This work addresses the challenge of a robot using real-time feedback from contact sensors to reliably manipulate a movable object on a cluttered tabletop. We formulate contact man…
Learning Dynamic Robot-to-Human Object Handover from Human Feedback
Andras Kupcsik, David Hsu, Wee Sun Lee
Object handover is a basic, but essential capability for robots interacting with humans in many applications, e.g., caring for the elderly and assisting workers in manufacturing wo…
POMDP-lite for Robust Robot Planning under Uncertainty
Min Chen, Emilio Frazzoli, David Hsu +1
The partially observable Markov decision process (POMDP) provides a principled general model for planning under uncertainty. However, solving a general POMDP is computationally int…