Dadu-Corki: Algorithm-Architecture Co-Design for Embodied AI-powered Robotic Manipulation
Yiyang Huang, Yuhui Hao, Yu Bo, Feng Yan, Yuxin Yang, Min Feng, Yinhe Han, Lin Ma, Shaoshan Liu, Qiang Liu, Yiming Gan · 2025
Embodied AI robots have the potential to fundamentally improve the way human beings live and manufacture.Continued progress in the burgeoning field of using large language models to control robots depends critically on an efficient computing substrate, and this trend is strongly evident in manipulation tasks.In particular, today's computing systems for embodied AI robots for manipulation tasks are designed purely based on the interest of algorithm developers, where robot actions are divided into a discrete frame basis.Such an execution pipeline creates high latency and energy consumption.This paper proposes Corki, an algorithm-architecture co-design framework for real-time embodied AI-powered robotic manipulation applications.We aim to decouple LLM inference, robotic control, and data communication in the embodied AI robots' compute pipeline.Instead of predicting action for one single frame, * equal contribution.