Multi-agent path finding visualizer

Multi-Agent Path Finding (MAPF) is a fundamental problem of planning paths for multi-agents where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Furthermore, there exist multiple algorithms used to solve the problem w.r.t mult...

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Main Author: Tran, Anh Tai
Other Authors: Tang Xueyan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156425
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1564252022-04-20T01:33:01Z Multi-agent path finding visualizer Tran, Anh Tai Tang Xueyan School of Computer Science and Engineering SCALE@NTU ASXYTang@ntu.edu.sg Engineering::Computer science and engineering Multi-Agent Path Finding (MAPF) is a fundamental problem of planning paths for multi-agents where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Furthermore, there exist multiple algorithms used to solve the problem w.r.t multiple extended versions of the initial MAPF problem. However, to the best of my knowledge, there does not exist any platform allowing the users to visualize the detail paths of the agents dynamically w.r.t various maps and agent locations. To develop a new algorithm for MAPF, individual researchers must conduct their own experiments set up which is very inconvenient. Thus, there is a need for a centralized interface that could allow the researcher to test their own algorithm w.r.t different maps and agent locations. As a web application, the MAPF Visualizer will offer features like adding the new agent locations, changing the map as well as visualizing the paths of those agents w.r.t different algorithms in a map and their setup locations. The author will also propose a small improvement of the implementation of one algorithm named conflict-based search. Bachelor of Engineering (Computer Science) 2022-04-16T11:34:54Z 2022-04-16T11:34:54Z 2022 Final Year Project (FYP) Tran, A. T. (2022). Multi-agent path finding visualizer. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156425 https://hdl.handle.net/10356/156425 en SCSE21-0111 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::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Tran, Anh Tai
Multi-agent path finding visualizer
description Multi-Agent Path Finding (MAPF) is a fundamental problem of planning paths for multi-agents where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Furthermore, there exist multiple algorithms used to solve the problem w.r.t multiple extended versions of the initial MAPF problem. However, to the best of my knowledge, there does not exist any platform allowing the users to visualize the detail paths of the agents dynamically w.r.t various maps and agent locations. To develop a new algorithm for MAPF, individual researchers must conduct their own experiments set up which is very inconvenient. Thus, there is a need for a centralized interface that could allow the researcher to test their own algorithm w.r.t different maps and agent locations. As a web application, the MAPF Visualizer will offer features like adding the new agent locations, changing the map as well as visualizing the paths of those agents w.r.t different algorithms in a map and their setup locations. The author will also propose a small improvement of the implementation of one algorithm named conflict-based search.
author2 Tang Xueyan
author_facet Tang Xueyan
Tran, Anh Tai
format Final Year Project
author Tran, Anh Tai
author_sort Tran, Anh Tai
title Multi-agent path finding visualizer
title_short Multi-agent path finding visualizer
title_full Multi-agent path finding visualizer
title_fullStr Multi-agent path finding visualizer
title_full_unstemmed Multi-agent path finding visualizer
title_sort multi-agent path finding visualizer
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156425
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