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Path Planning Based on Potential Fields from Rough Mereology

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10314))

Abstract

This paper focuses on path planning for a remote robotic agent using rough mereology potential field method. We test the proposed path-creation and path-finding algorithms and propose working alternative versions. Furthermore we apply path smoothing with custom collision detection to further optimize the route from the robot initial position to the goal.

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References

  1. Polkowski, L.: Rough mereology: a new paradigm for approximate reasoning. Int. J. Approx. Reason. 15(4), 333–365 (1996)

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  10. NXT Python. https://github.com/Eelviny/nxt-python

  11. The result of tests in the video. https://youtu.be/UrGvUoj_yeI

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Acknowledgements

This research has been supported by a grant 23.610.007-300 from the Ministry of Science and Higher Education of the Republic of Poland, and grant 23.620.0010-300 for young scientists from Department of Mathematics and Computer Sciences of University of Warmia and Mazury in Olsztyn.

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Correspondence to Piotr Artiemjew .

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Zmudzinski, L., Artiemjew, P. (2017). Path Planning Based on Potential Fields from Rough Mereology. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-60840-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60839-6

  • Online ISBN: 978-3-319-60840-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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