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Smoothing of Robotic Navigation Trajectories, Based on a Tessellation Generated Weighted Skeleton, Based on Wavefront Dilation and Collisions

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1274)

Abstract

Discretization processes adapted to robotic configuration spaces designed to limit the possible positions and movements of a robot in a continuous environment, have been based mainly on four methods for robotic motion planning: potential fields based, cell decomposition, roadmaps and sampling. However, these methods are not suitable for finding smooth routes through obstacles, and at he same time, avoiding collisions and taking into account the dimensions of the robot. This work proposes a new tessellation method using Bézier curves, which facilitates drawing of smooth curves while respecting restrictions imposed by the environment. The method takes into account the dimensions of the robot and, through a vector description of the configuration space, it constructs a skeleton of the configuration space between obstacles, where each point of the skeleton, in addition to having information on its coordinate, includes information about the transverse distance between objects at each point of the skeleton.

Keywords

  • Voronoi diagrams
  • Tessellation
  • Bezier curves
  • Navigation

Fundación Universitaria Los Libertadores, Universidad Nacional de Colombia, Universidad Tecnológica de Bolívar.

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References

  1. Ubiquitous sensor networks (USN) (2018). https://www.itu.int/dms$_$pub/itu-t/oth/23/01/T23010000040001PDFE.pdf. Accessed 22 June 2020

  2. Barraquand, J., Latombe, J.C.: Robot motion planning: a distributed representation approach. Int. J. Robot. Res. IJRR 10, 628–649 (1991). https://doi.org/10.1177/027836499101000604

    CrossRef  Google Scholar 

  3. Brunette, E.S., Flemmer, R.C., Flemmer, C.L.: A review of artificial intelligence. In: 2009 4th International Conference on Autonomous Robots and Agents, pp. 385–392 (2009)

    Google Scholar 

  4. Delling, D., Sanders, P., Schultes, D., Wagner, D.: Engineering route planning algorithms. In: Lerner, J., Wagner, D., Zweig, K.A. (eds.) Algorithmics of Large and Complex Networks. LNCS, vol. 5515, pp. 117–139. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02094-0_7

    CrossRef  Google Scholar 

  5. Kawabata, K., Ma, L., Xue, J., Chengwei, Z., Zheng, N.: A path generation for automated vehicle based on Bezier curve and via-points. Robot. Auton. Syst. 74 (2015). https://doi.org/10.1016/j.robot.2015.08.001

  6. Milos, S., Pich, V.: Robot motion planning using generalised voronoi diagrams, pp. 215–220, August 2008

    Google Scholar 

  7. Mo, H., Xu, L.: Research of biogeography particle swarm optimization for robot path planning. Neurocomputing 148(C), 91–99 (2015)

    CrossRef  Google Scholar 

  8. Ravankar, A., Ravankar, A., Kobayashi, Y., Emaru, T.: Avoiding blind leading the blind: uncertainty integration in virtual pheromone deposition by robots. Int. J. Adv. Robot. Syst. 13 (2016). https://doi.org/10.1177/1729881416666088

  9. Ravankar, A., Ravankar, A., Kobayashi, Y., Emaru, T.: Symbiotic navigation in multi-robot systems with remote obstacle knowledge sharing. Sensors 17, 1581 (2017). https://doi.org/10.3390/s17071581

    CrossRef  Google Scholar 

  10. Ravankar, A., Ravankar, A.A., Kobayashi, Y., Hoshino, Y., Peng, C.C.: Path smoothing techniques in robot navigation: state-of-the-art, current and future challenges. Sensors (Basel, Switzerland) 18, 3170 (2018)

    CrossRef  Google Scholar 

  11. Silva Ortigoza, R., et al.: Wheeled mobile robots: a review. IEEE Lat. Am. Trans. 10(6), 2209–2217 (2012)

    CrossRef  Google Scholar 

  12. Suhbrajit, B.: Topological and geometric techniques in graph search-based robot planning (2012)

    Google Scholar 

  13. Vu, A., Ramanandan, A., Chen, A., Farrell, J.A., Barth, M.: Real-time computer vision/DGPS-aided inertial navigation system for lane-level vehicle navigation. IEEE Trans. Intell. Transp. Syst. 13(2), 899–913 (2012)

    CrossRef  Google Scholar 

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Correspondence to I. Ladino , O. Penagos , B. Sáenz-Cabezas or Y. Pastrana .

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Ladino, I., Penagos, O., Sáenz-Cabezas, B., Pastrana, Y. (2020). Smoothing of Robotic Navigation Trajectories, Based on a Tessellation Generated Weighted Skeleton, Based on Wavefront Dilation and Collisions. In: Figueroa-García, J.C., Garay-Rairán, F.S., Hernández-Pérez, G.J., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2020. Communications in Computer and Information Science, vol 1274. Springer, Cham. https://doi.org/10.1007/978-3-030-61834-6_9

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  • DOI: https://doi.org/10.1007/978-3-030-61834-6_9

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-61834-6

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