SP-NN: A novel neural network approach for path planning

Shuai Li; Max Q.H. Meng; Wanming Chen; Yangming Li; Zhuhong You; Yajin Zhou; Lei Sun; Huawei Liang; Kai Jiang; Qinglei Guo

doi:10.1109/ROBIO.2007.4522361

SP-NN: A novel neural network approach for path planning

Shuai Li, Max Q.H. Meng, Wanming Chen, Yangming Li, Zhuhong You, Yajin Zhou, Lei Sun, Huawei Liang, Kai Jiang, Qinglei Guo

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

21 Citations (Scopus)

Abstract

In this paper, a neural network approach named shortest path neural networks (SP-NN) is proposed for real-time on-line path planning. Based on grid-based map and mapping this kind of map to neural networks, this proposed method is capable of generating the globally shortest path from the target position to the start position without collision with any obstacles. The dynamics of each neuron is distinctive to other previously presented methods by other researchers and ensures that the generated path is shortest without collision and that the state of neurons varied continuously. Extensive simulations show the efficiency of the presented method.

Original language	English
Title of host publication	2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
Publisher	IEEE Computer Society
Pages	1355-1360
Number of pages	6
ISBN (Print)	9781424417582
DOIs	https://doi.org/10.1109/ROBIO.2007.4522361
Publication status	Published - 1 Jan 2007
Externally published	Yes
Event	2007 IEEE International Conference on Robotics and Biomimetics, ROBIO - Yalong Bay, Sanya, China Duration: 15 Dec 2007 → 18 Dec 2007

Conference

Conference	2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
Country/Territory	China
City	Yalong Bay, Sanya
Period	15/12/07 → 18/12/07

Keywords

Labyrinth environment
Mobile robot
Neural networks
On-line planning
Path planning

ASJC Scopus subject areas

Artificial Intelligence
Control and Systems Engineering
Biomaterials

More information

10.1109/ROBIO.2007.4522361

Cite this

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title = "SP-NN: A novel neural network approach for path planning",

abstract = "In this paper, a neural network approach named shortest path neural networks (SP-NN) is proposed for real-time on-line path planning. Based on grid-based map and mapping this kind of map to neural networks, this proposed method is capable of generating the globally shortest path from the target position to the start position without collision with any obstacles. The dynamics of each neuron is distinctive to other previously presented methods by other researchers and ensures that the generated path is shortest without collision and that the state of neurons varied continuously. Extensive simulations show the efficiency of the presented method.",

keywords = "Labyrinth environment, Mobile robot, Neural networks, On-line planning, Path planning",

author = "Shuai Li and Meng, {Max Q.H.} and Wanming Chen and Yangming Li and Zhuhong You and Yajin Zhou and Lei Sun and Huawei Liang and Kai Jiang and Qinglei Guo",

year = "2007",

month = jan,

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doi = "10.1109/ROBIO.2007.4522361",

language = "English",

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pages = "1355--1360",

booktitle = "2007 IEEE International Conference on Robotics and Biomimetics, ROBIO",

publisher = "IEEE Computer Society",

address = "United States",

note = "2007 IEEE International Conference on Robotics and Biomimetics, ROBIO ; Conference date: 15-12-2007 Through 18-12-2007",

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Li, S, Meng, MQH, Chen, W, Li, Y, You, Z, Zhou, Y, Sun, L, Liang, H, Jiang, K & Guo, Q 2007, SP-NN: A novel neural network approach for path planning. in 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO., 4522361, IEEE Computer Society, pp. 1355-1360, 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO, Yalong Bay, Sanya, China, 15/12/07. https://doi.org/10.1109/ROBIO.2007.4522361

SP-NN: A novel neural network approach for path planning. / Li, Shuai; Meng, Max Q.H.; Chen, Wanming et al.
2007 IEEE International Conference on Robotics and Biomimetics, ROBIO. IEEE Computer Society, 2007. p. 1355-1360 4522361.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Meng, Max Q.H.

AU - Chen, Wanming

AU - Li, Yangming

AU - You, Zhuhong

AU - Zhou, Yajin

AU - Sun, Lei

AU - Liang, Huawei

AU - Jiang, Kai

AU - Guo, Qinglei

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AB - In this paper, a neural network approach named shortest path neural networks (SP-NN) is proposed for real-time on-line path planning. Based on grid-based map and mapping this kind of map to neural networks, this proposed method is capable of generating the globally shortest path from the target position to the start position without collision with any obstacles. The dynamics of each neuron is distinctive to other previously presented methods by other researchers and ensures that the generated path is shortest without collision and that the state of neurons varied continuously. Extensive simulations show the efficiency of the presented method.

KW - Labyrinth environment

KW - Mobile robot

KW - Neural networks

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KW - Path planning

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BT - 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO

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SP-NN: A novel neural network approach for path planning

Abstract

Conference

Keywords

ASJC Scopus subject areas

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