10 citations · 10 across the 5 of their papers we have counts for
6 papers
Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment
Nina Moorman, Julianna Schalkwyk, Vriksha Srihari +6
Learning from demonstration (LfD) methods enable non-expert end users to teach robots novel skills without explicit programming. However most evaluations of the usability of LfD wi…
Decoupled Hierarchical Reinforcement Learning with State Abstraction for Discrete Grids
Qingyu Xiao, Yuanlin Chang, Youtian Du
Effective agent exploration remains a core challenge in reinforcement learning (RL) for complex discrete state-space environments, particularly under partial observability. This pa…
Learning Wheelchair Tennis Navigation from Broadcast Videos with Domain Knowledge Transfer and Diffusion Motion Planning
Zixuan Wu, Zulfiqar Zaidi, Adithya Patil +2
In this paper, we propose a novel and generalizable zero-shot knowledge transfer framework that distills expert sports navigation strategies from web videos into robotic systems wi…
Learning Dynamics of a Ball with Differentiable Factor Graph and Roto-Translational Invariant Representations
Qingyu Xiao, Zixuan Wu, Matthew Gombolay
Robots in dynamic environments need fast, accurate models of how objects move in their environments to support agile planning. In sports such as ping pong, analytical models often…
Learning Diverse Robot Striking Motions with Diffusion Models and Kinematically Constrained Gradient Guidance
Kin Man Lee, Sean Ye, Qingyu Xiao +5
Advances in robot learning have enabled robots to generate skills for a variety of tasks. Yet, robot learning is typically sample inefficient, struggles to learn from data sources…
Multi-Camera Asynchronous Ball Localization and Trajectory Prediction with Factor Graphs and Human Poses
Qingyu Xiao, Zulfiqar Zaidi, Matthew Gombolay
The rapid and precise localization and prediction of a ball are critical for developing agile robots in ball sports, particularly in sports like tennis characterized by high-speed…