12 citations · 24 across the 8 of their papers we have counts for
4 papers · 1 filter
Multi-Task Learning with Sequence-Conditioned Transporter Networks
Michael H. Lim, Andy Zeng, Brian Ichter +5
Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling th…
Ensemble Augmentation for Deep Neural Networks Using 1-D Time Series Vibration Data
Atik Faysal, Ngui Wai Keng, M. H. Lim
Time-series data are one of the fundamental types of raw data representation used in data-driven techniques. In machine condition monitoring, time-series vibration data are overly…
Voronoi Progressive Widening: Efficient Online Solvers for Continuous State, Action, and Observation POMDPs
Michael H. Lim, Claire J. Tomlin, Zachary N. Sunberg
This paper introduces Voronoi Progressive Widening (VPW), a generalization of Voronoi optimistic optimization (VOO) and action progressive widening to partially observable Markov d…
Sparse tree search optimality guarantees in POMDPs with continuous observation spaces
Michael H. Lim, Claire J. Tomlin, Zachary N. Sunberg
Partially observable Markov decision processes (POMDPs) with continuous state and observation spaces have powerful flexibility for representing real-world decision and control prob…