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Improved Potential Field Method for Robot Path Planning with Path Pruning

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Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 (NUSYS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 666))

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Abstract

Path planning is vital for a robot deployed in a mission in a challenging environment with obstacles around. The robot needs to ensure that the mission is accomplished without colliding with any obstacles and find an optimal path to reach the goal. Three important criteria, i.e., path length, computational complexity, and completeness, need to be taken into account when designing a path planning method. Artificial Potential Field (APF) is one of the best methods for path planning as it is fast, simple, and elegant. However, the APF has a major problem called local minima, which will cause the robot fails to reach the goal. This paper proposed an Improved Potential Field method to solve the APF limitation. Despite that, the path length produced by the Improved APF is not optimal. Therefore, a path pruning technique is proposed in order to shorten the path generated by the Improved APF. This paper also compares the performance on the path length and computational time of the Improved APF with and without path pruning. Through simulation, it is proven that the proposed technique could overcome the local minima problem and produces a relatively shorter path with fast computation time.

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References

  1. Hasircioglu I, Topcuoglu HR, Ermis M (2008) 3-D path planning for the navigation of unmanned aerial vehicles by using evolutionary algorithms. In: Proceedings of the conference on genetic and evolutionary computation, pp 1499–1506

    Google Scholar 

  2. Omar RB (2011) Path planning for unmanned aerial vehicles using visibility line-based methods. control and instrumentation research group. Department of Engineering, University of Leicester, March 2011

    Google Scholar 

  3. Sabudin EN, Omar R, Che Ku Melor CKANH (2016) Potential field methods and their inherent approaches for path planning. ARPN J Eng Appl Sci 11(18):10801–10805

    Google Scholar 

  4. Borenstein J, Koren Y (1991) Potential field methods and their inherent limitations for mobile robot navigation, April 1991, pp 1398–1404

    Google Scholar 

  5. Cen Y, Wang L, Zhang H (2007) Real-time obstacle avoidance strategy for mobile robot based on improved coordinating potential field with genetic algorithm. In: IEEE international conference on control applications, October 2007

    Google Scholar 

  6. Lifen AL, Rouxin BS, Shuandao CL, Jiang DW (2016) Path planning for UAVS based on improved artificial potential field method through changing the repulsive potential function. In: IEEE Chinese guidance, navigation and control conference (CGNCC), 12–14 August 2016

    Google Scholar 

  7. Liu Y, Zhao Y (2016) A virtual-waypoint based artificial potential field method for UAV path planning. In: Proceedings of 2016 IEEE Chinese guidance, navigation and control conference, 12–14 August 2016

    Google Scholar 

  8. Khatib O (1985) Real-time obstacle avoidance for manipulators and mobile robots. In: Proceedings of the IEEE international conference on robotics and automation, pp 500–505

    Google Scholar 

  9. Mei W, Su Z, Tu D, Lu X (2013) A hybrid algorithm based on artificial potential field and BUG for path planning of mobile robot. In: 2nd international conference on measurement, information and control

    Google Scholar 

  10. Wang S, Min H (2013) Experience mixed the modified artificial potential field method. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), 3–7 November 2013

    Google Scholar 

  11. Mei JH, Arshad MR (2015) A balance-artificial potential field method for autonomous surface vessel navigation in unstructured riverine environment. In: IEEE international symposium on robotics and intelligent sensors (IRIS)

    Google Scholar 

  12. Li G, Tamura Y, Yamashita A, Asama H (2012) Effective improved artificial potential field-based regression search method for robot planning. In: IEEE international conference on mechatronic and automation, 5–8 August 2012

    Google Scholar 

  13. Li G, Tamura Y, Yamashita A, Asama H (2013) Effective improved artificial potential field-based regression search method for autonomous mobile robot path planning. Int J Mechatron Autom 3(3):141–170

    Article  Google Scholar 

  14. Sfeir J, Saad M, Saliah-Hasane H (2011) An improved potential field approach to real-time mobile robot path planning in an unknown environment. In: IEEE international symposium on robotic and sensors environments (ROSE)

    Google Scholar 

  15. Park JW, Kwak HJ, Kang YC, Kim DW (2016) Advanced fuzzy potential field method for mobile robot obstacle avoidance. J Comput Intell Neurosci 2016. Article No. 10

    Google Scholar 

  16. Godrich MA. Potential Field Tutorial. https://pdfs.semanticscholar.org/725e/fa1af22f41dcbecd8bd445ea82679a6eb7c6.pdf. Accessed 29 Aug 2019

  17. Robot Motion Planning and Control. Potential Field. https://sebastian-hoeffner.de/uni/ceng786/index.php?number=2. Accessed 29 Aug 2019

  18. Debnath SK, Omar RB, Abdul Latip NB (2019) A review on energy efficient path planning algorithms for unmanned air vehicles. In: Computational science and technology. Springer, Singapore

    Google Scholar 

  19. Omar RB, Che Ku Melor CKNAH, Sabudin EN (2015) Performance comparison of path planning methods. ARPN J Eng Appl Sci

    Google Scholar 

  20. Li G, Tong S, Lv G, Xiao R, Cong F, Tong Z, Yamashita A, Asama H (2015) An improved artificial potential field-based simultaneous forward search (improved APF-based SIFORS) method for robot path planning. In: The 12th international conference on ubiquitous robots and ambient intelligence (URAI), 28–30 October 2015

    Google Scholar 

Download references

Acknowledgements

Authors like to give appreciations to Universiti Tun Hussein Onn Malaysia (UTHM) and Research Management Center (RMC) for supporting fund under TIER-1 VOT H131.

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Authors and Affiliations

  1. Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Elia Nadira Sabudin, Rosli Omar, Ariffudin Joret, Asmarashid Ponniran, Herdawatie Abdul Kadir & Sanjoy Kumar Debnath

  2. Power Electronic Converters (PECs) Focus Group, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Asmarashid Ponniran

  3. Faculty of Technical and Vocational Education, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Ariffudin Joret & Muhammad Suhaimi Sulong

  4. Internet of Things (IOT) Focus Group, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Muhammad Suhaimi Sulong

Authors
  1. Elia Nadira Sabudin
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  2. Rosli Omar
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  3. Ariffudin Joret
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  4. Asmarashid Ponniran
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  5. Muhammad Suhaimi Sulong
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  6. Herdawatie Abdul Kadir
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  7. Sanjoy Kumar Debnath
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Corresponding author

Correspondence to Rosli Omar .

Editor information

Editors and Affiliations

  1. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Zainah Md Zain

  2. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Hamzah Ahmad

  3. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Dwi Pebrianti

  4. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Mahfuzah Mustafa

  5. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Nor Rul Hasma Abdullah

  6. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Rosdiyana Samad

  7. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Maziyah Mat Noh

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Cite this paper

Sabudin, E.N. et al. (2021). Improved Potential Field Method for Robot Path Planning with Path Pruning. In: Md Zain, Z., et al. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 . NUSYS 2019. Lecture Notes in Electrical Engineering, vol 666. Springer, Singapore. https://doi.org/10.1007/978-981-15-5281-6_9

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