1 citations · 1 across the 7 of their papers we have counts for
7 papers
Efficiently Learning Robust Torque-based Locomotion Through Reinforcement with Model-Based Supervision
Yashuai Yan, Tobias Egle, Christian Ott +1
We propose a control framework that integrates model-based bipedal locomotion with residual reinforcement learning (RL) to achieve robust and adaptive walking in the presence of re…
Learning a Unified Latent Space for Cross-Embodiment Robot Control
Yashuai Yan, Dongheui Lee
We present a scalable framework for cross-embodiment humanoid robot control by learning a shared latent representation that unifies motion across humans and diverse humanoid platfo…
Variable Stiffness for Robust Locomotion through Reinforcement Learning
Dario Spoljaric, Yashuai Yan, Dongheui Lee
Reinforcement-learned locomotion enables legged robots to perform highly dynamic motions but often accompanies time-consuming manual tuning of joint stiffness. This paper introduce…
Enhancing Model-Based Step Adaptation for Push Recovery through Reinforcement Learning of Step Timing and Region
Tobias Egle, Yashuai Yan, Dongheui Lee +1
This paper introduces a new approach to enhance the robustness of humanoid walking under strong perturbations, such as substantial pushes. Effective recovery from external disturba…
I-CTRL: Imitation to Control Humanoid Robots Through Constrained Reinforcement Learning
Yashuai Yan, Esteve Valls Mascaro, Tobias Egle +1
Humanoid robots have the potential to mimic human motions with high visual fidelity, yet translating these motions into practical, physical execution remains a significant challeng…
Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction
Esteve Valls Mascaro, Yashuai Yan, Dongheui Lee
Integrating robots into populated environments is a complex challenge that requires an understanding of human social dynamics. In this work, we propose to model social motion forec…
ImitationNet: Unsupervised Human-to-Robot Motion Retargeting via Shared Latent Space
Yashuai Yan, Esteve Valls Mascaro, Dongheui Lee
This paper introduces a novel deep-learning approach for human-to-robot motion retargeting, enabling robots to mimic human poses accurately. Contrary to prior deep-learning-based w…