Simultaneous localization and mapping (SLAM) is a quintessential problem in autonomous navigation, augmented reality, and virtual reality. In particular, low-power SLAM has gained increasing importance for its applications in power-limited edge devices such as unmanned aerial vehicles (UAVs) and small-sized cars that constitute devices with edge intelligence. This article presents a 7.25-to-8.79-TOPS/W mixed-signal oscillator-based SLAM accelerator for applications in edge robotics. This study proposes a neuromorphic SLAM IC, called NeuroSLAM, employing oscillator-based pose-cells and a digital head direction cell to mimic place cells and head direction cells that have been discovered in a rodent brain. The oscillatory network emulates a spiking neural network and its continuous attractor property achieves spatial cognition with a sparse energy distribution, similar to the brains of rodents. Furthermore, a lightweight vision system with a max-pooling is implemented to support low-power visual odometry and re-localization. The test chip fabricated in a 65-nm CMOS exhibits a peak energy efficiency of 8.79 TOPS/W with a power consumption of 23.82 mW.

中文翻译：

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NeuroSLAM：一种用于边缘机器人的基于 65 纳米 7.25 至 8.79 TOPS/W 混合信号振荡器的 SLAM 加速器

同时定位和映射 (SLAM) 是自主导航、增强现实和虚拟现实中的典型问题。特别是，低功耗 SLAM 因其在功率受限的边缘设备中的应用而变得越来越重要，例如构成具有边缘智能的设备的无人驾驶飞行器 (UAV) 和小型汽车。本文介绍了一种基于 7.25 至 8.79-TOPS/W 混合信号振荡器的 SLAM 加速器，适用于边缘机器人技术。这项研究提出了一种称为 NeuroSLAM 的神经形态 SLAM IC，它采用基于振荡器的姿势细胞和数字头部方向细胞来模拟在啮齿动物大脑中发现的位置细胞和头部方向细胞。振荡网络模拟尖峰神经网络，其连续吸引子特性以稀疏的能量分布实现空间认知，类似于啮齿动物的大脑。此外，实现了具有最大池化的轻量级视觉系统以支持低功耗视觉里程计和重新定位。采用 65-nm CMOS 制造的测试芯片的峰值能效为 8.79 TOPS/W，功耗为 23.82 mW。