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Paper Abstract and Keywords
Presentation 2024-11-28 13:50
Likelihood-based spatial-modeling for capturing micro-mobility vehicles in LIDAR sensor network
Kazufumi Suzuki, Ryoichi Shinkuma, Gabriele Trovato (SIT) SRW2024-29 SeMI2024-41
Abstract (in Japanese) (See Japanese page) 
(in English) Urbanization and technological innovation are driving increased demand for public transportation, with autonomous micro-mobility vehicles expected to proliferate in response to labor shortages and the need for decarbonization.The concept of the digital twin is anticipated to play a pivotal role in enabling the coexistence of these vehicles, and the construction of LiDAR sensor networks on the infrastructure side is under consideration to support this development.While LiDAR sensor networks are crucial for ensuring the safety of autonomous micro-mobility, the sparse point clouds generated by LiDAR often lead to incomplete representations of objects, particularly for thin, narrow, or small objects.To address this issue, we present a method for constructing a spatial model of the target object, introducing the concept of "likelihood", which represents the probability of an object's presence at each spatial location.This report demonstrates the effectiveness of our method through experiments conducted with actual LiDAR sensors, comparing its performance to benchmark methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Digital twin technology / LiDAR sensor network / Point cloud upsampling / Autonomous micro-mobility / Spatial model / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 277, SeMI2024-41, pp. 13-14, Nov. 2024.
Paper # SeMI2024-41 
Date of Issue 2024-11-21 (SRW, SeMI) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SRW2024-29 SeMI2024-41

Conference Information
Committee SRW SeMI  
Conference Date 2024-11-28 - 2024-11-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Univ. of Science Katsushika Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IoT Workshop 
Paper Information
Registration To SeMI 
Conference Code 2024-11-SRW-SeMI 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Likelihood-based spatial-modeling for capturing micro-mobility vehicles in LIDAR sensor network 
Sub Title (in English)  
Keyword(1) Digital twin technology  
Keyword(2) LiDAR sensor network  
Keyword(3) Point cloud upsampling  
Keyword(4) Autonomous micro-mobility  
Keyword(5) Spatial model  
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1st Author's Name Kazufumi Suzuki  
1st Author's Affiliation Shibaura Institute of technology (SIT)
2nd Author's Name Ryoichi Shinkuma  
2nd Author's Affiliation Shibaura Institute of technology (SIT)
3rd Author's Name Gabriele Trovato  
3rd Author's Affiliation Shibaura Institute of technology (SIT)
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Speaker Author-1 
Date Time 2024-11-28 13:50:00 
Presentation Time 25 minutes 
Registration for SeMI 
Paper # SRW2024-29, SeMI2024-41 
Volume (vol) vol.124 
Number (no) no.276(SRW), no.277(SeMI) 
Page pp.13-14 
#Pages 2 
Date of Issue 2024-11-21 (SRW, SeMI) 

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