A 1.1 mW 32-thread artificial intelligence processor with 3-level transposition table and on-chip PVT compensation for autonomous mobile robots

Youchang Kim, Dongjoo Shin, Jinsu Lee, H. Yoo
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Abstract

An ultra-low-power multi-threaded artificial intelligence processor (AIP) is proposed for real-time autonomous navigation of mobile robots. To achieve real-time operation under low power consumption, the proposed AIP adopts 3 key features: 1) an 8-thread tree search processor (TSP) for real-time path planning, 2) a 3-level transposition table cache (TT$) for the reduction of duplicated computations, and 3) an on-chip PVT compensation circuit (PVTC) for energy-efficient operation at near-threshold supply voltage. As a result, it achieves 470,000 state/s search speed and 79 nJ/search energy consumption which are 9.4× and 11× better than the general-purpose CPUs currently used in recent mobile robots. In addition, the AIP is successfully applied to the robots for autonomous navigation without any collision in dynamic environments.
一种1.1 mW 32线程人工智能处理器,具有3级换位表和片上PVT补偿
提出了一种用于移动机器人实时自主导航的超低功耗多线程人工智能处理器(AIP)。为了实现低功耗下的实时运行,提出的AIP采用了3个关键特征:1)8线程树搜索处理器(TSP)用于实时路径规划;2)3级换位表缓存(TT$)用于减少重复计算;3)片上PVT补偿电路(PVTC)用于近阈值电源电压下的节能运行。实现了470,000状态/s的搜索速度和79 nJ/s的搜索能耗,分别比目前移动机器人中使用的通用cpu高9.4倍和11倍。此外,还成功地将AIP应用于机器人在动态环境中实现无碰撞自主导航。
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