6 papers
Forecast-Aware Cooperative Planning on Temporal Graphs under Stochastic Adversarial Risk
Manshi Limbu, Xuan Wang, Gregory J. Stein +2
Cooperative multi-robot missions often require teams of robots to traverse environments where traversal risk evolves due to adversary patrols or shifting hazards with stochastic dy…
Geometry-Aligned LLM Fine-Tuning for Sequential Narrow-Opening Planning
Al Jaber Mahmud, Xuan Wang
We study rigid-body motion planning through multiple sequential narrow openings, which requires long-horizon geometric reasoning because the configuration used to traverse an early…
CARoL: Context-aware Adaptation for Robot Learning
Zechen Hu, Tong Xu, Xuesu Xiao +1
Using Reinforcement Learning (RL) to learn new robotic tasks from scratch is often inefficient. Leveraging prior knowledge has the potential to significantly enhance learning effic…
Heterogeneous Team Coordination on Partially Observable Graphs with Realistic Communication
Yanlin Zhou, Manshi Limbu, Xuan Wang +2
Team Coordination on Graphs with Risky Edges (\textsc{tcgre}) is a recently proposed problem, in which robots find paths to their goals while considering possible coordination to r…
Multi-Robot Coordination Induced in an Adversarial Graph-Traversal Game
James Berneburg, Xuan Wang, Xuesu Xiao +1
This paper presents a game theoretic formulation of a graph traversal problem, with applications to robots moving through hazardous environments in the presence of an adversary, as…
Learning Coordinated Maneuver in Adversarial Environments
Zechen Hu, Manshi Limbu, Daigo Shishika +2
This paper aims to solve the coordination of a team of robots traversing a route in the presence of adversaries with random positions. Our goal is to minimize the overall cost of t…