9 papers
Scalable Rao-Blackwellized Online Planning for High-Dimensional POMDPs
Jiho Lee, Nisar Ahmed, Kyle Hollins Wray +1
Online planning under uncertainty remains a fundamental challenge for robotic systems operating in partially observable environments with high-dimensional state spaces. While sampl…
GOLEM: Modular Humanoid Autonomy Towards Electric Vehicle Battery Disassembly
Max Conway, William Xie, Allen Devaraj +14
Disassembling end-of-life electric vehicle (EV) battery packs is dull and dangerous work, performed almost entirely by humans. We present GOLEM (Generalized Open Library of Embodie…
Beyond Fixed Goal Delivery: Online POMDP Planning for Target Interception in Crowds
Himanshu Gupta, Kelvin Aladum, Nisar Ahmed +2
Target interception in crowded environments requires reaching a moving objective while navigating among multiple uncertain human agents. Since human navigation intent is not direct…
Efficient Multi-Robot Motion Planning with Precomputed Translation-Invariant Edge Bundles
Himanshu Gupta, Paul Motter, Aritra Chakrabarty +5
Solving multi-robot motion planning (MRMP) requires generating collision-free kinodynamically feasible trajectories for multiple interacting robots. We introduce Kinodynamic Transl…
Simultaneous AlphaZero: Extending Tree Search to Markov Games
Tyler Becker, Zachary Sunberg
Many strategic planning problems require agents to act simultaneously, making turn-based search unsuitable and requiring a normal form game to be solved at each tree state. We intr…
Resolving Multiple-Dynamic Model Uncertainty in Hypothesis-Driven Belief-MDPs
Ofer Dagan, Tyler Becker, Zachary N. Sunberg
When human operators of cyber-physical systems encounter surprising behavior, they often consider multiple hypotheses that might explain it. In some cases, taking information-gathe…
Rao-Blackwellized POMDP Planning
Jiho Lee, Nisar R. Ahmed, Kyle H. Wray +1
Partially Observable Markov Decision Processes (POMDPs) provide a structured framework for decision-making under uncertainty, but their application requires efficient belief update…
Bridging the Gap between Partially Observable Stochastic Games and Sparse POMDP Methods
Tyler Becker, Zachary Sunberg
Many real-world decision problems involve the interaction of multiple self-interested agents with limited sensing ability. The partially observable stochastic game (POSG) provides…
Simultaneous active parameter estimation and control using sampling-based Bayesian reinforcement learning
Patrick Slade, Preston Culbertson, Zachary Sunberg +1
Robots performing manipulation tasks must operate under uncertainty about both their pose and the dynamics of the system. In order to remain robust to modeling error and shifts in…