Kin Man Lee — accepted AI-conference papers

2025

Learning Diverse Robot Striking Motions with Diffusion Models and Kinematically Constrained Gradient Guidance

Kin Man Lee, Sean Ye, Qingyu Xiao, Zixuan Wu, Zulfiqar Zaidi, David B. D'Ambrosio +2

ICRA 2025

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 exhibiting varied behaviors, and does not naturally incorporate constraints. These properties are critical for fast, agi

Cited by 8 Source ↗Scholar ↗

2023

Athletic Mobile Manipulator System for Robotic Wheelchair Tennis

Zulfiqar Zaidi, Daniel Martin, Nathaniel Belles, Viacheslav Zakharov, Arjun Krishna, Kin Man Lee +17

RA-L 2023

Athletics are a quintessential and universal expression of humanity. From French monks who in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$12{\text{th}}$</tex-math></inline-formula> century invented <italic

Cited by 25 Source ↗code ↗Scholar ↗