Wenhao Yu
I obtained my PhD in Computer Science from Georgia Institute of Technology advised by Karen Liu and Greg Turk.
My research lies at the intersection of computer graphics, robotics, and machine learning. I develop learning-based algorithms for acquiring motor skills for animated characters and transfer learning algorithms for transferring learned skills from simulation to real robots and novel environments. My research goal is to enable simulated characters and real robots to learn highly-dynamic movements in complex environments in an automatic, efficient, and generalizable way.
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Zero-Shot Retargeting of Learned Quadruped Locomotion Policy Using A Hybrid Kinodynamic Model and Predictive Control
He Li
Patrick Wensing
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022) (2022) (to appear)
Learning Semantic-Aware Locomotion Skills from Human Demonstration
Byron Boots
Xiangyun Meng
Yuxiang Yang
Conference on Robot Learning (CoRL) 2022 (2022) (to appear)
Style-Augmented Mutual Information for Practical Skill Discovery
Ale Escontrela
Jason Peng
Ken Goldberg
Pieter Abbeel
Proceedings of NeurIPS (2022) (to appear)
PI-ARS: Accelerating Evolution-Learned Visual Locomotion with Predictive Information Representations
Ofir Nachum
International Conference on Intelligent Robots and Systems (IROS) (2022)
Safe Reinforcement Learning for Legged Locomotion
Jimmy Yang
Peter J. Ramadge
Sehoon Ha
International Conference on Robotics and Automation (2022) (to appear)
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions
Ale Escontrela
Jason Peng
Ken Goldberg
Pieter Abbeel
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (2022) (to appear)
Learning to walk on complex terrains with vision
Ale Escontrela
Erwin Johan Coumans
Peng Xu
Sehoon Ha
Conference on Robotic Learning (2021)
Learning Fast Adaptation with Meta Strategy Optimization
Erwin Johan Coumans
Sehoon Ha
Learning Fast Adaptation with Meta Strategy Optimization (2020)
