17 citations · 27 across the 13 of their papers we have counts for
9 papers · 1 filter
Diffusion Policy for Coordinated Control of a Nonholonomic Mobile Base and Dual Arms in Door Opening and Passing
Shangqun Yu, Matthew En, Daniel Wu +4
Opening heavy, self closing doors, especially those that require pulling remains a long standing challenge in robotics. Humans naturally employ both arms in a dexterous manner, rot…
Human-Centered Development of Guide Dog Robots: Quiet and Stable Locomotion Control
Shangqun Yu, Hochul Hwang, Trung M. Dang +4
A quadruped robot is a promising system that can offer assistance comparable to that of dog guides due to its similar form factor. However, various challenges remain in making thes…
A Biomechanics-Inspired Approach to Soccer Kicking for Humanoid Robots
Daniel Marew, Nisal Perera, Shangqun Yu +2
Soccer kicking is a complex whole-body motion that requires intricate coordination of various motor actions. To accomplish such dynamic motion in a humanoid robot, the robot needs…
Learning Generic and Dynamic Locomotion of Humanoids Across Discrete Terrains
Shangqun Yu, Nisal Perera, Daniel Marew +1
This paper addresses the challenge of terrain-adaptive dynamic locomotion in humanoid robots, a problem traditionally tackled by optimization-based methods or reinforcement learnin…
Impedance Matching: Enabling an RL-Based Running Jump in a Quadruped Robot
Neil Guan, Shangqun Yu, Shifan Zhu +1
Replicating the remarkable athleticism seen in animals has long been a challenge in robotics control. Although Reinforcement Learning (RL) has demonstrated significant progress in…
StaccaToe: A Single-Leg Robot that Mimics the Human Leg and Toe
Nisal Perera, Shangqun Yu, Daniel Marew +6
We introduce StaccaToe, a human-scale, electric motor-powered single-leg robot designed to rival the agility of human locomotion through two distinctive attributes: an actuated toe…
Integration of Riemannian Motion Policy with Whole-Body Control for Collision-Free Legged Locomotion
Daniel Marew, Misha Lvovsky, Shangqun Yu +2
In this paper, we present a Riemannian Motion Policy (RMP)flow-based whole-body control framework for improved dynamic legged locomotion. RMPflow is a differential geometry-inspire…
Hierarchical Reinforcement Learning of Locomotion Policies in Response to Approaching Objects: A Preliminary Study
Shangqun Yu, Sreehari Rammohan, Kaiyu Zheng +1
Animals such as rabbits and birds can instantly generate locomotion behavior in reaction to a dynamic, approaching object, such as a person or a rock, despite having possibly never…
Value-Based Reinforcement Learning for Continuous Control Robotic Manipulation in Multi-Task Sparse Reward Settings
Sreehari Rammohan, Shangqun Yu, Bowen He +4
Learning continuous control in high-dimensional sparse reward settings, such as robotic manipulation, is a challenging problem due to the number of samples often required to obtain…