4 papers · 1 filter
POMDPs for Autonomous Science Exploration
Daniel Guirguis, Nathan Wallace, Hanna Kurniawati +1
Autonomous exploration missions require decision-making under sensor uncertainty and computational constraints, yet integrating scientific representations into POMDP planning has r…
Think Fast and Far: Long-Horizon Online POMDP Planning via Rapid State Sampling
Yuanchu Liang, Edward Kim, J. Arden Knoll +4
Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalabil…
POMDP-based Object Search with Growing State Space and Hybrid Action Domain
Yongbo Chen, Hesheng Wang, Shoudong Huang +1
Efficiently locating target objects in complex indoor environments with diverse furniture, such as shelves, tables, and beds, is a significant challenge for mobile robots. This dif…
Scaling Long-Horizon Online POMDP Planning via Rapid State Space Sampling
Yuanchu Liang, Edward Kim, Wil Thomason +3
Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalabil…