Koshi Makihara

A modular benchmark that adapts to diverse insertion scenarios reveals critical insights into robotic generalization capabilities in high-precision tasks.

The embodiment gap reveals that even advanced robot foundation models require substantial adaptation to function on specific robotic platforms, challenging the assumption that scaling alone suffices for generalization.