神经形态工程学
里程计
人工智能
同时定位和映射
机器人学
计算机科学
视觉里程计
计算机视觉
GSM演进的增强数据速率
机器人
人工神经网络
移动机器人
作者
Jae-Hyun Lee,Jong-Hyeok Yoon
标识
DOI:10.1109/isocc56007.2022.10031388
摘要
Ultra-low-power SLAM has been of importance for edge devices to achieve extensive exploration under a GPS-restricted environment. Visual SLAM on edge devices suffers from accumulated odometry errors until re-localization occurs. This paper presents a neuromorphic SLAM accelerator supporting multi-agent error correction for applications in swarm robotics. The proposed multi-agent neuromorphic SLAM (MAN-SLAM) accelerator suppresses odometry errors by multi-agent map optimization. The MAN-SLAM accelerator employs time-domain spiking neural networks and emulates continuous attractor networks. The proposed MAN-SLAM demonstrates robust SLAM performance under the outdoor exploration of real environments.
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