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Shengtao Li

3 accepted papers

2025

Think on Your Feet: Seamless Transition Between Human-Like Locomotion in Response to Changing Commands

ICRA 2025

While it is relatively easier to train humanoid robots to mimic specific locomotion skills, it is more challenging to learn from various motions and adhere to continuously changing commands. These robots must accurately track motion instructions, seamlessly transition between a variety of movements,

Cited by 2SourceScholar
2024

Adapting Humanoid Locomotion over Challenging Terrain via Two-Phase Training

CoRL 2024poster

Humanoid robots are a key focus in robotics, with their capacity to navigate tough terrains being essential for many uses. While strides have been made, creating adaptable locomotion for complex environments is still tough. Recent progress in learning-based systems offers hope for robust legged loco…

Cited by 4SourceScholar
2024

GridFormer: Point-Grid Transformer for Surface Reconstruction

AAAI 2024technical

Implicit neural networks have emerged as a crucial technology in 3D surface reconstruction. To reconstruct continuous surfaces from discrete point clouds, encoding the input points into regular grid features (plane or volume) has been commonly employed in existing approaches. However, these methods…