A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics

Jaehyun Lee; Jong Hyeok Yoon

doi:10.1109/ISOCC56007.2022.10031388

A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics

Jaehyun Lee
, Jong Hyeok Yoon

Department of Electrical Engineering and Computer Science

Daegu Gyeongbuk Institute of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings - International SoC Design Conference 2022, ISOCC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	241-242
Number of pages	2
ISBN (Electronic)	9781665459716
DOIs	https://doi.org/10.1109/ISOCC56007.2022.10031388
State	Published - 2022
Event	19th International System-on-Chip Design Conference, ISOCC 2022 - Gangneung-si, Korea, Republic of Duration: 19 Oct 2022 → 22 Oct 2022

Publication series

Name	Proceedings - International SoC Design Conference 2022, ISOCC 2022

Conference

Conference	19th International System-on-Chip Design Conference, ISOCC 2022
Country/Territory	Korea, Republic of
City	Gangneung-si
Period	19/10/22 → 22/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

continuous attractor network
multiagent error correction
simultaneous localization and mapping
spiking neural network
swarm robotics
visual odometry

Access to Document

10.1109/ISOCC56007.2022.10031388

Cite this

Lee, J., & Yoon, J. H. (2022). A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics. In Proceedings - International SoC Design Conference 2022, ISOCC 2022 (pp. 241-242). (Proceedings - International SoC Design Conference 2022, ISOCC 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISOCC56007.2022.10031388

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title = "A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics",

abstract = "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.",

keywords = "continuous attractor network, multiagent error correction, simultaneous localization and mapping, spiking neural network, swarm robotics, visual odometry",

author = "Jaehyun Lee and Yoon, \{Jong Hyeok\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th International System-on-Chip Design Conference, ISOCC 2022 ; Conference date: 19-10-2022 Through 22-10-2022",

year = "2022",

doi = "10.1109/ISOCC56007.2022.10031388",

language = "English",

series = "Proceedings - International SoC Design Conference 2022, ISOCC 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Lee, J & Yoon, JH 2022, A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics. in Proceedings - International SoC Design Conference 2022, ISOCC 2022. Proceedings - International SoC Design Conference 2022, ISOCC 2022, Institute of Electrical and Electronics Engineers Inc., pp. 241-242, 19th International System-on-Chip Design Conference, ISOCC 2022, Gangneung-si, Korea, Republic of, 19/10/22. https://doi.org/10.1109/ISOCC56007.2022.10031388

A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics. / Lee, Jaehyun; Yoon, Jong Hyeok.
Proceedings - International SoC Design Conference 2022, ISOCC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 241-242 (Proceedings - International SoC Design Conference 2022, ISOCC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

KW - continuous attractor network

KW - multiagent error correction

KW - simultaneous localization and mapping

KW - spiking neural network

KW - swarm robotics

KW - visual odometry

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M3 - Conference contribution

AN - SCOPUS:85148467672

T3 - Proceedings - International SoC Design Conference 2022, ISOCC 2022

SP - 241

EP - 242

BT - Proceedings - International SoC Design Conference 2022, ISOCC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th International System-on-Chip Design Conference, ISOCC 2022

Y2 - 19 October 2022 through 22 October 2022

ER -

A Neuromorphic SLAM Accelerator Supporting Multi-Agent Error Correction in Swarm Robotics

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Bibliographical note

Keywords

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