Jiahang Cao

A function-preserving Real-to-Sim-to-Real framework that generates synthetic demonstrations from reconstructed assets without teleoperated source trajectories is proposed, enabling robust generalization across unseen object geometries and diverse visual conditions in contact-rich and long-horizon tasks.

SOLO achieves a remarkable 97.5% mean traversal success on complex terrains, showcasing a leap in humanoid locomotion capabilities.

Humanoid robots can now adapt to complex terrains in real-time by leveraging detailed plantar pressure feedback, achieving remarkable performance even on unseen surfaces.