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The article presents a novel framework for teaching quadrupedal robots aggressive locomotion skills using only monocular videos, bypassing the need for expensive motion capture systems. It utilizes robust 2D pose estimation and a Spatio-Temporal Graph Convolution Network to reconstruct 3D joint trajectories, enabling the robots to learn complex motions such as galloping and backflipping. The proposed method significantly enhances robotic locomotion capabilities while reducing data collection costs and compl

Author

xugq1014

Language

EN