7 papers
Continuous-Time Gaussian Belief Trees for Motion Planning
Rayan Mazouz, Qi Heng Ho, Zachary N. Sunberg +1
We address sampling-based motion planning for continuous-time stochastic systems under process and measurement uncertainty, with probabilistic guarantees on safety and performance.…
Robustness Analysis of POMDP Policies to Observation Perturbations
Benjamin Kraske, Qi Heng Ho, Federico Rossi +2
Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviate from the true system durin…
Leveraging the Value of Information in POMDP Planning
Zakariya Laouar, Qi Heng Ho, Zachary Sunberg
Partially observable Markov decision processes (POMDPs) offer a principled formalism for planning under state and transition uncertainty. Despite advances made towards solving larg…
Sampling-based Task and Kinodynamic Motion Planning under Semantic Uncertainty
Qi Heng Ho, Zachary N. Sunberg, Morteza Lahijanian
This paper tackles the problem of integrated task and kinodynamic motion planning in uncertain environments. We consider a robot with nonlinear dynamics tasked with a Linear Tempor…
Feasibility-Guided Safety-Aware Model Predictive Control for Jump Markov Linear Systems
Zakariya Laouar, Qi Heng Ho, Rayan Mazouz +2
In this paper, we present a controller framework that synthesizes control policies for Jump Markov Linear Systems subject to stochastic mode switches and imperfect mode estimation.…
Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives
Qi Heng Ho, Martin S. Feather, Federico Rossi +2
Partially Observable Markov Decision Processes (POMDPs) are powerful models for sequential decision making under transition and observation uncertainties. This paper studies the ch…