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Towards a More Accurate Time of Flight Distance Sensor to Be Applied in a Mobile Robotics Application

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Proceedings TEEM 2022: Tenth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM 2022)

Abstract

In this paper, it is presented a field of view analysis of a time of flight sensor, that will be applied in a mobile robotics application. The sensor was configured in order to obtain a tradeoff between reactiveness and accuracy. It was used a microcontroller development board to acquire data and a manipulator to perform the movements, assuring repeatability and accuracy in the data acquisition process. The results of this paper will be used as an input to a simulation, in order to assist in the development of a mobile robotics application and also to be applied in educational contexts.

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References

  1. Li, L.: et al.: Time-of-flight camera–an introduction. Technical white paper, no. SLOA190B (2014)

    Google Scholar 

  2. Vl53l0x datasheet - stmicroelectronics. https://www.alldatasheet.com/datasheet-pdf/pdf/948120/STMICROELECTRONICS/VL53L0X.html?mo. Accessed 03 Jan 2022

  3. Lindner, M., Schiller, I., Kolb, A., Koch, R.: Time-of-flight sensor calibration for accurate range sensing. Comput. Vis. Image Underst. 114(12), 1318–1328 (2010)

    Article  Google Scholar 

  4. Seiter, J., Hofbauer, M., Davidovic, M., Zimmermann, H.: FPGA based time-of-flight 3D camera characterization system. In: 2013 IEEE 16th International Symposium on Design and Diagnostics of Electronic Circuits & Systems (DDECS), pp. 240–245. IEEE (2013)

    Google Scholar 

  5. Campos, D., Santos, J., Gonçalves, J., Costa, P.: Modeling and simulation of a hacked neato XV-11 laser scanner. In: Robot 2015: Second Iberian Robotics Conference. AISC, vol. 417, pp. 425–436. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-27146-0_33

    Chapter  Google Scholar 

  6. Gonçalves, J., Lima, J., Oliveira, H., Costa, P.: Sensor and actuator modeling of a realistic wheeled mobile robot simulator. In: 2008 IEEE International Conference on Emerging Technologies and Factory Automation, pp. 980–985. IEEE (2008)

    Google Scholar 

  7. Fuchs, S.: Calibration and multipath mitigation for increased accuracy of time-of-flight camera measurements in robotic applications (2012)

    Google Scholar 

  8. Malheiros, P., Gonçalves, J., Costa, P.: Towards a more accurate infrared distance sensor model. Manufacturing Systems Engineering Unit (2009)

    Google Scholar 

  9. Paulo, C., José, G., José, L., Paulo, M.: SimTwo realistic simulator: a tool for the development and validation of robot software. Theor. Appl. Math. Comput. Sci. 1(1), 17–33 (2011)

    Google Scholar 

  10. Camargo, C., Gonçalves, J., Conde, M.Á., Rodríguez-Sedano, F.J., Costa, P., García-Peñalvo, F.J.: Systematic literature review of realistic simulators applied in educational robotics context. Sensors 21(12), 4031 (2021)

    Article  Google Scholar 

  11. Brancalião, L., Conde, M., Costa, P., Gonçalves, J.: Stochastic modeling of a time of flight sensor to be applied in a mobile robotics application (2022)

    Google Scholar 

  12. Kassow robots - kr810. https://www.kassowrobots.com/products/kr810/. Accessed 03 Jan 2022

  13. Lazarus homepage. https://www.lazarus-ide.org/. Accessed 03 Jan 2022

  14. McKinney, W., et al.: Pandas: a foundational python library for data analysis and statistics. Python High Perform. Sci. Comput. 14(9), 1–9 (2011)

    Google Scholar 

  15. 15 python libraries for data science you should know. https://www.dataquest.io/blog/15-python-libraries-for-data-science/. Accessed 03 Feb 2022

  16. Picamera release-1.13. https://picamera.readthedocs.io/en/release-1.13/. Accessed 06 Jan 2022

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Acknowledgement

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.

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Correspondence to Laiany Brancalião .

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Brancalião, L., Alvarez, M., Conde, M.Á., Costa, P., Gonçalves, J. (2023). Towards a More Accurate Time of Flight Distance Sensor to Be Applied in a Mobile Robotics Application. In: García-Peñalvo, F.J., García-Holgado, A. (eds) Proceedings TEEM 2022: Tenth International Conference on Technological Ecosystems for Enhancing Multiculturality. TEEM 2022. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-99-0942-1_121

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  • DOI: https://doi.org/10.1007/978-981-99-0942-1_121

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  • Online ISBN: 978-981-99-0942-1

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