Vision assisted object detection In LIDAR point cloud

In 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...

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Main Author: Yuen, Wei Chee
Other Authors: Xie Lihua
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158702
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1587022023-07-07T18:59:19Z Vision assisted object detection In LIDAR point cloud Yuen, Wei Chee Xie Lihua School of Electrical and Electronic Engineering ELHXIE@ntu.edu.sg Engineering::Electrical and electronic engineering In 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. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-06-07T02:58:29Z 2022-06-07T02:58:29Z 2022 Final Year Project (FYP) Yuen, W. C. (2022). Vision assisted object detection In LIDAR point cloud. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158702 https://hdl.handle.net/10356/158702 en A1186-211 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Yuen, Wei Chee
Vision assisted object detection In LIDAR point cloud
description In 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.
author2 Xie Lihua
author_facet Xie Lihua
Yuen, Wei Chee
format Final Year Project
author Yuen, Wei Chee
author_sort Yuen, Wei Chee
title Vision assisted object detection In LIDAR point cloud
title_short Vision assisted object detection In LIDAR point cloud
title_full Vision assisted object detection In LIDAR point cloud
title_fullStr Vision assisted object detection In LIDAR point cloud
title_full_unstemmed Vision assisted object detection In LIDAR point cloud
title_sort vision assisted object detection in lidar point cloud
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158702
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