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Autonomous Localization of Missing Items with Aerial Robots in an Aircraft Factory

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ROBOT 2017: Third Iberian Robotics Conference (ROBOT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 694))

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Abstract

Missing tools is a problem in aircraft factories. It may reduce the productivity of the assembly line and missing items may cause FOD (Foreign Object Damage) if they are lost inside the aerostructure. This paper proposes a method which uses aerial robots to search and locate missing tools. Each tool will be equipped with a radio tag with an ID that can listen and respond to request messages from the aerial robot. Thus, the robot can take range measurements to the missing tools from different locations while performing other tasks in the factory. The range measurements are used to estimate the location of every missing tool using a Particle Filter (PF) which will eventually converge to an Extended Kalman Filter (EKF). The proposed method was evaluated and validated in real experiments performed in an emulated scenario very similar to the real factory. Preliminary tests were also performed in the Airbus DS CBC factory with good results.

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Notes

  1. 1.

    Swiss Federal Institute of Technology in Zurich: https://www.ethz.ch/en.html.

  2. 2.

    Center for Advanced Aerospace Technologies: http://www.catec.aero/en.

  3. 3.

    http://www.euroc-project.eu/.

References

  1. Blumenthal, J., Grossmann, R., Golatowski, F., Timmermann, D.: Weighted centroid localization in Zigbee-based sensor networks. In: 2007 IEEE International Symposium on Intelligent Signal Processing, WISP 2007, pp. 1–6. IEEE (2007)

    Google Scholar 

  2. Kantor, G., Singh, S.: Preliminary results in range-only localization and mapping. In: 2002 IEEE International Conference on Robotics and Automation, Proceedings, ICRA 2002, vol. 2, pp. 1818–1823. IEEE (2002)

    Google Scholar 

  3. Menegatti, E., Zanella, A., Zilli, S., Zorzi, F., Pagello, E.: Range-only SLAM with a mobile robot and a wireless sensor networks. In: IEEE International Conference on Robotics and Automation, ICRA, pp. 8–14 (2009)

    Google Scholar 

  4. Patwari, N., O’Dea, R.J., Wang, Y.: Relative location in wireless networks. In: 2001 IEEE VTS 53rd Vehicular Technology Conference, VTC 2001 Spring, vol. 2, pp. 1149–1153. IEEE (2001)

    Google Scholar 

  5. Pfaff, P., Plagemann, C., Burgard, W.: Gaussian mixture models for probabilistic localization. In: 2008 IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 467–472. IEEE (2008)

    Google Scholar 

  6. Pitt, M.K., Shephard, N.: Filtering via simulation: auxiliary particle filters. J. Am. Stat. Assoc. 94(446), 590–599 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  7. Stoleru, R., Stankovic, J.A.: Probability grid: a location estimation scheme for wireless sensor networks. In: 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004, IEEE SECON 2004, pp. 430–438. IEEE (2004)

    Google Scholar 

  8. Thrun, S., Fox, D., Burgard, W., Dellaert, F.: Robust monte carlo localization for mobile robots. Artif. Intell. 128(1–2), 99–141 (2001)

    Article  MATH  Google Scholar 

  9. Torres-González, A., Martinez-de Dios, J.R., Ollero, A.: An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements. Sensors 14(5), 7684–7710 (2014)

    Article  Google Scholar 

  10. Wang, X., Bischoff, O., Laur, R., Paul, S.: Localization in wireless Ad-hoc sensor networks using multilateration with RSSI for logistic applications. Procedia Chem. 1(1), 461–464 (2009)

    Article  Google Scholar 

  11. Wessels, A., Wang, X., Laur, R., Lang, W.: Dynamic indoor localization using multilateration with RSSI in wireless sensor networks for transport logistics. Procedia Eng. 5, 220–223 (2010)

    Article  Google Scholar 

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Acknowledgements

This work has received funding from the European Union under grant agreement No. 608849 (EUROC).

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Correspondence to Julio L. Paneque .

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Paneque, J.L., Torres-González, A., Dios, J.R.Md., Ramírez, J.R.A., Ollero, A. (2018). Autonomous Localization of Missing Items with Aerial Robots in an Aircraft Factory. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_15

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  • DOI: https://doi.org/10.1007/978-3-319-70836-2_15

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  • Online ISBN: 978-3-319-70836-2

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