Path planning for unmanned automaton based on improved artificial potential field method

Research Article
Open access

Path planning for unmanned automaton based on improved artificial potential field method

Feiyi Jin 1*
  • 1 East China University of Science and Technology    
  • *corresponding author 21011263@mail.ecust.edu.cn
Published on 25 September 2023 | https://doi.org/10.54254/2755-2721/10/20230163
ACE Vol.10
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-009-7
ISBN (Online): 978-1-83558-010-3

Abstract

The artificial potential field method (APF), a highly effective navigation technique, is currently utilized extensively in this area due to the rapid development of unmanned automatons. Traditional APF, however, have several shortcomings, including the issue of unreachable object points and the propensity to sink into local minima that prohibit the automaton from moving on. In this paper, a two-part improved APF model is created to address these issues. First, by including additional constraints, the repulsive field model at the stumbling block is enhanced to address the issue that the object point is impassable when too close a distance between the two stumbling blocks. Secondly, a new potential field is introduced to help the automaton walk out of the local minima. Analogue simulation show that the methods mentioned above can solve these problems better and make the route planning of unmanned automatons come true.

Keywords:

unmanned robot, artificial potential field, path planning.

Jin,F. (2023). Path planning for unmanned automaton based on improved artificial potential field method. Applied and Computational Engineering,10,120-128.
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References

[1]. Zhang, H. Y., Lin, W. M., and Chen, A. X. 2018 Path planning for the mobile robot: A review. Symmetry, 10(10), 450.

[2]. Yang, L., Qi, J., Xiao, J., and Yong, X. 2014 A literature review of UAV 3D path planning. Proceeding of the 11th World Congress on Intelligent Control and Automation (pp. 2376-2381). IEEE.

[3]. Gu Donglei, Li Xiaoge, Wang Shuo. 2014 Path planning method for mobile robots. Robotics and Applications, (1):28-30.

[4]. Sang, H., You, Y., Sun, X., Zhou, Y., and Liu, F. 2021 The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations. Ocean Engineering, 223, 108709.

[5]. Shin, Y., and Kim, E. 2021. Hybrid path planning using positioning risk and artificial potential fields. Aerospace Science and Technology, 112, 106640.

[6]. Lin, X., Wang, Z. Q., and Chen, X. Y. 2020, May. Path planning with improved artificial potential field method based on decision tree. 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS) (pp. 1-5). IEEE.

[7]. DING Jiaru, DU Changping, ZHAO Yao and YIN Dengyu. 2016 UAV path planning algorithm based on improved artificial potential field method. Computer Applications (01),287-290.

[8]. ZHAO Ming, ZHENG Zeyu, MO Qingfeng, PAN Yijun and LIU Zhi. 2020 Path planning method of mobile robot based on improved artificial potential field method. Computer Application Research (S2), 66-68+72.

[9]. ZHANG Jianying, ZHAO Zhiping and LIU Yun. 2006 Robot path planning based on artificial potential field method. Journal of Harbin Institute of Technology (08),1306-1309.

[10]. Khatib, O. 1985 Real-time obstacle avoidance for manipulators and mobile robots. In Proceedings. 1985 IEEE international conference on robotics and automation (Vol. 2, pp. 500-505). IEEE.

[11]. LUO Qiang, WANG Haibao,CUI Xiaojin and HE Jingchang. 2019 Improve the path planning of autonomous mobile robots by artificial potential field method. Control Engineering (06),1091-1098.

Cite this article

Jin,F. (2023). Path planning for unmanned automaton based on improved artificial potential field method. Applied and Computational Engineering,10,120-128.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Mechatronics and Smart Systems

ISBN：978-1-83558-009-7(Print) / 978-1-83558-010-3(Online)
Editor：Alan Wang, Seyed Ghaffar
Conference website: https://2023.confmss.org/
Conference date: 24 June 2023
Series: Applied and Computational Engineering
Volume number: Vol.10
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Zhang, H. Y., Lin, W. M., and Chen, A. X. 2018 Path planning for the mobile robot: A review. Symmetry, 10(10), 450.

[2]. Yang, L., Qi, J., Xiao, J., and Yong, X. 2014 A literature review of UAV 3D path planning. Proceeding of the 11th World Congress on Intelligent Control and Automation (pp. 2376-2381). IEEE.

[3]. Gu Donglei, Li Xiaoge, Wang Shuo. 2014 Path planning method for mobile robots. Robotics and Applications, (1):28-30.

[4]. Sang, H., You, Y., Sun, X., Zhou, Y., and Liu, F. 2021 The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations. Ocean Engineering, 223, 108709.

[5]. Shin, Y., and Kim, E. 2021. Hybrid path planning using positioning risk and artificial potential fields. Aerospace Science and Technology, 112, 106640.

[6]. Lin, X., Wang, Z. Q., and Chen, X. Y. 2020, May. Path planning with improved artificial potential field method based on decision tree. 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS) (pp. 1-5). IEEE.

[7]. DING Jiaru, DU Changping, ZHAO Yao and YIN Dengyu. 2016 UAV path planning algorithm based on improved artificial potential field method. Computer Applications (01),287-290.

[8]. ZHAO Ming, ZHENG Zeyu, MO Qingfeng, PAN Yijun and LIU Zhi. 2020 Path planning method of mobile robot based on improved artificial potential field method. Computer Application Research (S2), 66-68+72.

[9]. ZHANG Jianying, ZHAO Zhiping and LIU Yun. 2006 Robot path planning based on artificial potential field method. Journal of Harbin Institute of Technology (08),1306-1309.

[10]. Khatib, O. 1985 Real-time obstacle avoidance for manipulators and mobile robots. In Proceedings. 1985 IEEE international conference on robotics and automation (Vol. 2, pp. 500-505). IEEE.

[11]. LUO Qiang, WANG Haibao,CUI Xiaojin and HE Jingchang. 2019 Improve the path planning of autonomous mobile robots by artificial potential field method. Control Engineering (06),1091-1098.

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