Zhong Shen

Robot hardware has traditionally focused on speed, payload, precision, and actuator performance. Yet as robot intelligence rapidly evolves—from imitation learning to VLA models, world models, and end-to-end approaches—hardware must adapt to changing software architectures while remaining reliable over years of deployment.

Through the development of Taku, we explore this challenge from three perspectives: Reliable Foundation, Robust Interfaces, and Accelerated Iteration.