One paper accepted by ICRA 2025!
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Research
Currently, my research interest includes reinforcement learning, robotics and generative models. I am also open to explore other research topics. Some papers are highlighted.
MoELoco introduces a multitask locomotion framework that employs a mixture-of-experts strategy to enhance reinforcement learning across diverse tasks while leveraging compositionality to generate new skills.
VR-Robo introduces a digital twin framework using 3D Gaussian Splatting for photorealistic simulation, enabling RGB-based sim-to-real transfer for robot navigation and locomotion.
We propose a proprioception-only, two-stage training framework with goal command and a dedicated tiny trap benchmark, enabling quadruped robots to robustly traverse small obstacles.
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