Zhiyuan Zhang

Enforcing symmetry equivariance in bimanual robot learning yields policies that are not only more performant but also significantly more robust to distribution shifts, a crucial step towards reliable real-world deployment.

Tactile force fields unlock robust robotic disassembly, outperforming vision-only and even naive RGB-tactile fusion, particularly in deformable and contact-rich scenarios.