Place recognition and re-localization for last-mile delivery robot

The need for delivery services has increased due to the growth of e-commerce and online shopping, making it more difficult for delivery companies to compete. Among the procedure, the last-mile delivery issue is the trickiest and most expensive part. To solve it, one approach is the use of delivery r...

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Main Author: Xu, Lihaotian
Other Authors: Wang Dan Wei
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/168056
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1680562023-07-07T17:37:59Z Place recognition and re-localization for last-mile delivery robot Xu, Lihaotian Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering The need for delivery services has increased due to the growth of e-commerce and online shopping, making it more difficult for delivery companies to compete. Among the procedure, the last-mile delivery issue is the trickiest and most expensive part. To solve it, one approach is the use of delivery robots, which have a number of advantages over conventional delivery techniques. However, in order to perform daily distribution activities, last-mile delivery robots need a precise and dependable self-positioning mechanism. This paper introduces the concept of SLAM (Simultaneous Localization and Mapping) as a technique used in robotics and computer vision to address the issue of mapping an unknown environment while also figuring out where the robot is in that environment. The paper implements a SLAM algorithm (SC-LIO-SAM) on a delivery robot and verifies its performance by running various datasets. Experimental results show that the proposed framework has good precision, recall and viewpoint robustness on both public benchmark and self-built campus datasets. Paper also concludes that LiDAR-based SLAM algorithm have the potential to significantly improve the performance of last-mile delivery robots and lead to more efficient, reliable delivery operations. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-06-06T08:16:27Z 2023-06-06T08:16:27Z 2023 Final Year Project (FYP) Xu, L. (2023). Place recognition and re-localization for last-mile delivery robot. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/168056 https://hdl.handle.net/10356/168056 en 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
Xu, Lihaotian
Place recognition and re-localization for last-mile delivery robot
description The need for delivery services has increased due to the growth of e-commerce and online shopping, making it more difficult for delivery companies to compete. Among the procedure, the last-mile delivery issue is the trickiest and most expensive part. To solve it, one approach is the use of delivery robots, which have a number of advantages over conventional delivery techniques. However, in order to perform daily distribution activities, last-mile delivery robots need a precise and dependable self-positioning mechanism. This paper introduces the concept of SLAM (Simultaneous Localization and Mapping) as a technique used in robotics and computer vision to address the issue of mapping an unknown environment while also figuring out where the robot is in that environment. The paper implements a SLAM algorithm (SC-LIO-SAM) on a delivery robot and verifies its performance by running various datasets. Experimental results show that the proposed framework has good precision, recall and viewpoint robustness on both public benchmark and self-built campus datasets. Paper also concludes that LiDAR-based SLAM algorithm have the potential to significantly improve the performance of last-mile delivery robots and lead to more efficient, reliable delivery operations.
author2 Wang Dan Wei
author_facet Wang Dan Wei
Xu, Lihaotian
format Final Year Project
author Xu, Lihaotian
author_sort Xu, Lihaotian
title Place recognition and re-localization for last-mile delivery robot
title_short Place recognition and re-localization for last-mile delivery robot
title_full Place recognition and re-localization for last-mile delivery robot
title_fullStr Place recognition and re-localization for last-mile delivery robot
title_full_unstemmed Place recognition and re-localization for last-mile delivery robot
title_sort place recognition and re-localization for last-mile delivery robot
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/168056
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