Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158702
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYuen, Wei Cheeen_US
dc.date.accessioned2022-06-07T02:58:29Z-
dc.date.available2022-06-07T02:58:29Z-
dc.date.issued2022-
dc.identifier.citationYuen, W. C. (2022). Vision assisted object detection In LIDAR point cloud. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158702en_US
dc.identifier.urihttps://hdl.handle.net/10356/158702-
dc.description.abstractIn the age of Industry 4.0, the usage of autonomous guided robots has become a commonplace, especially in logistics, transport and manufacturing. With more labor-intensive operations being highly automated as a solution to improve the efficiency of manufacturing processes, autonomous guided vehicles (AGVs) are deployed to facilitate transportation of materials and finished products. The key to success is to develop a robust and secure avoidance policy for robots, therefore ensuring the safe maneuverability of the robot. The usage of a 2D LiDAR only for object collision avoidance results in frequent stop in navigation due to lack of target identification. Therefore, this project focuses on the training of a lightweight object detection model and the alignment of a LiDAR point cloud with the object detection model based on the live video footage from the RGB camera to provide a vision assisted object detection to enable the AGV to navigate and avoid obstacles in a dynamic environment. It is able to continuously track the target object , while navigating through a dynamic environment, avoiding obstacles.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationA1186-211en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleVision assisted object detection In LIDAR point clouden_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorXie Lihuaen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
dc.contributor.supervisoremailELHXIE@ntu.edu.sgen_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
Yuen Wei Chee FYP Final Report DRNTU Submission.pdf
  Restricted Access
2.33 MBAdobe PDFView/Open

Page view(s)

59
Updated on Jan 31, 2023

Download(s)

11
Updated on Jan 31, 2023

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.