机器人AI芯片设计技术综述  

Review of AI chips design for robotics

作　　者：郜锦阳 樊震东 包敏杰 王珂[1] 李瑞峰[1] 康鹏 GAO Jinyang;FAN Zhendong;BAO Minjie;WANG Ke;LI Ruifeng;KANG Peng(State Key Laboratory of Robotics and Systems,Harbin Institute of Technology,Harbin 150001,China;Jianghuai Advance Technology Center,Hefei 230000,China)

机构地区：[1]哈尔滨工业大学机器人技术与系统全国重点实验室,哈尔滨150001 [2]江淮前沿技术协同创新中心,合肥230000

出　　处：《集成电路与嵌入式系统》2024年第11期60-77,共18页Integrated Circuits and Embedded Systems

基　　金：江淮前沿技术协同创新中心追梦基金课题(2023-ZM01Z026)。

摘　　要：机器人+人工智能将引领新智能技术变革,人工神经网络在机器人感知方面应用潜力巨大。然而,AI算法日益复杂、CPU等通用处理器能效瓶颈问题突出,传统处理芯片无法有效适配大规模神经网络的推理计算任务。近年来,机器人AI芯片凭借高算力、低功耗特性成为神经网络在机器人系统应用部署的理想选择,受到广泛关注。本文面向机器人应用,研究AI算法现状,梳理AI芯片设计技术最新进展,提出技术难点及可行技术路线,探讨机器人AI芯片设计的技术趋势及挑战。The combination of Robots and artificial intelligence will lead the transformation of new intelligent technologies.Furthermore,as a crucial component of artificial intelligence,neural networks demonstrate immense potential in robotic perception.However,the increasing complexity of AI algorithms and the prominent energy efficiency bottleneck of general-purpose processors such as CPUs pose significant challenges.Traditional processing chips fail to effectively accommodate the inference computing tasks of large-scale neural networks.In recent years,robotic AI chips,with high computing performance and low power consumption,have emerged as an ideal choice for deploying of neural networks in robot systems due to their,attracting widespread attention.This article focusing on robotic applications,studies the current status of AI algorithms,reviews the latest advances in AI chip design technology,proposes technical difficulties and feasible technical routes,and discusses the technical trends and challenges in the design of robotic AI chips.

关 键 词：机器人 人工神经网络 人工智能芯片 软硬件协同设计 硬件加速器 

分 类 号：TP872[自动化与计算机技术—检测技术与自动化装置]