A 2.793 μW near-threshold neuronal population dynamics trajectory filter for reliable simultaneous localization and mapping

• Main Authors: Wei, Zhengzhe, Dong, Boyi, Su, Yuqi, Wang, Yi, Yang, Chuanshi, Lu, Yuncheng, Wang, Chao, Kim, Tony Tae-Hyoung, Zheng, Yuanjin
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2025
• Subjects: Engineering; Simultaneous localization and mapping; Trajectory filter
• Online Access: https://hdl.handle.net/10356/182675
• Institution: Nanyang Technological University

This work presents an algorithm hardware co-design implementing a digital neuronal population dynamics simulator intended for the trajectory error correction task within a simultaneous localization and mapping workflow. A custom discretized procedural algorithm approximating a neuronal population dynamics-based inference operation is developed for mapping onto an ultra-lightweight digital macro featuring massively parallel in-situ processing techniques. Fabricated using a 40nm technology, the test chip features a 22×2 neuron array with 0.1358mm2 core area and provides a 12-bit computing precision. A time-multiplexed processing element design prevents the use of excessive silicon area. Accomplished via extensive data reuse through massively parallel processing-in-memory architecture attached to a custom I/O interface, a single inference operation is completed within 3277 clock cycles, providing 200 inferences per second operating at a low frequency of 0.667Mhz with a 0.5V core supply and consuming sub-10-μ W power.