Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/140352
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, Yongyao | en_US |
dc.date.accessioned | 2020-05-28T04:51:23Z | - |
dc.date.available | 2020-05-28T04:51:23Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | https://hdl.handle.net/10356/140352 | - |
dc.description.abstract | Human detection is an essential task for a SLAM system in dynamic environment, such as warehouses, where the robot shares its workspace and interacts closely with operating personnel. Being aware of the real-time locations of humans in the scene is the basis for safe operation of the system. This final year project presents a 3D LiDAR SLAM system with an efficient human classification function that utilizes human geometry and state-of-the-art machine learning techniques to accurately identify human clusters in complex 3D point clouds. The performance of the system is evaluated with firsthand data from the Delta-NTU Corporate Laboratory for Cyber-Physical Systems. Experiments show the combination of the anthropometric and SVM classifiers produces decent human classification results in warehouse environment with medium to high complexity. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nanyang Technological University | en_US |
dc.relation | A1241-191 | en_US |
dc.subject | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics | en_US |
dc.title | On-board 3-D SLAM for AGV localization | en_US |
dc.type | Final Year Project (FYP) | en_US |
dc.contributor.supervisor | Xie Lihua | en_US |
dc.contributor.school | School of Electrical and Electronic Engineering | en_US |
dc.description.degree | Bachelor of Engineering (Electrical and Electronic Engineering) | en_US |
dc.contributor.supervisoremail | ELHXIE@ntu.edu.sg | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
Appears in Collections: | EEE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FYP Final Report Chen Yongyao.pdf Restricted Access | 5.22 MB | Adobe PDF | View/Open |
Page view(s) 50
466
Updated on Mar 28, 2024
Download(s) 50
28
Updated on Mar 28, 2024
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.