Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)

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UAV Map Construction and Path Planning System based on SLAM Technology

Authors
Jinfeng Liang1, Simin Liu2, *
1School of Automation, China University Of Petroleum - BeijingAt Karamay, Karamay, 834099, China
2School of Process Equipment and Control Engineering, Dalian University of Technology, Panjin, 124221, China
*Corresponding author. Email: 17622892603@mail.dlut.edu.cn
Corresponding Author
Simin Liu
Available Online 16 October 2024.
DOI
10.2991/978-94-6463-540-9_39How to use a DOI?
Keywords
UAV; SLAM Algorithm; Path Planning
Abstract

In recent years, people’s technological advancement has led to the rapid development of drone technology, but there is still a long way to go before the realisation of drone technology that does not require a human to operate it. Currently, people’s drone technology is at the stage where it does not require humans to enter the cockpit to operate it, but only needs to be remotely controlled from a remote location. However, with the current level of science and technology, it is not yet possible for people to realise the autonomous path planning function of UAVs in unfamiliar environments and completely out of people’s control, relying only on their own fitted sensors to realise according to the coordinates and characteristics of the destination. Therefore, to address the problem that UAVs cannot realise autonomous obstacle avoidance, this paper proposes a new design idea to explore the feasibility of combining SLAM technology and UAV technology, so that UAVs can acquire the surrounding environmental data through visual and laser sensors and feedback the data to the SLAM system after being instructed. The SLAM system constructs a map model of the surrounding environment from the data returned, and uses the cell decomposition method and the artificial potential field method to carry out autonomous path planning on this map to achieve the effect of autonomous obstacle avoidance for UAVs.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
Series
Advances in Computer Science Research
Publication Date
16 October 2024
ISBN
978-94-6463-540-9
ISSN
2352-538X
DOI
10.2991/978-94-6463-540-9_39How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jinfeng Liang
AU  - Simin Liu
PY  - 2024
DA  - 2024/10/16
TI  - UAV Map Construction and Path Planning System based on SLAM Technology
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 393
EP  - 402
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_39
DO  - 10.2991/978-94-6463-540-9_39
ID  - Liang2024
ER  -