12 citations · 24 across the 8 of their papers we have counts for
8 papers
Multi-Agent Reachability Calibration with Conformal Prediction
Anish Muthali, Haotian Shen, Sampada Deglurkar +4
We investigate methods to provide safety assurances for autonomous agents that incorporate predictions of other, uncontrolled agents' behavior into their own trajectory planning. G…
Optimality Guarantees for Particle Belief Approximation of POMDPs
Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer +2
Partially observable Markov decision processes (POMDPs) provide a flexible representation for real-world decision and control problems. However, POMDPs are notoriously difficult to…
Navigation between initial and desired community states using shortcuts
Benjamin W. Blonder, Michael H. Lim, Zachary Sunberg +1
Ecological management problems often involve navigating from an initial to a desired community state. We ask whether navigation is possible without brute-force additions and deleti…
Compositional Learning-based Planning for Vision POMDPs
Sampada Deglurkar, Michael H. Lim, Johnathan Tucker +3
The Partially Observable Markov Decision Process (POMDP) is a powerful framework for capturing decision-making problems that involve state and transition uncertainty. However, most…
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…