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Development of an AlphaBot2 Simulator for RPi Camera and Infrared Sensors

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Robot 2019: Fourth Iberian Robotics Conference (ROBOT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1092))

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Abstract

In recent years robots have been used as a tool for teaching purposes, motivating the development of fully virtual environments for combined real/simulated robotics teaching. The AlphaBot2 Raspberry Pi (RPi), a robot used for education, has no currently available simulator. A Gazebo simulator was produced and a ROS framework was implemented for hardware abstraction and control of low-level modules facilitating students control of the robot’s physical behaviours in the real and simulated robot, simultaneously. For the demonstration of the basic model operation, an algorithm for detection of obstacles and lines was implemented for the IR sensors, however, some discrepancies in a line track timed test were detected justifying the need for further work in modelling and performance assessment. Despite that, the implemented ROS structure was verified to be functional in the simulation and the real AlphaBot2 for its motion control, through the input sensors and camera.

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References

  1. Davcev, K., Koceska, N., Koceski, S.: A review of robotic kits used for education purposes. In: International Conference on Information Technology and Development of Education – ITRO, Zrenjanin, Serbia, pp. 152–155, June 2019

    Google Scholar 

  2. Yusof, Y., Hassan, M.A., Mohd Saroni, N.J., Che Wan Azizan, W.M.F.: Development of an educational virtual mobile robot simulation (2011)

    Google Scholar 

  3. Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G.: Robotics: Modelling, Planning and Control. Springer, London (2010)

    Google Scholar 

  4. Pepper, C.T., Balakirsky, S.B., Scrapper Jr., C.J.: Robot simulation physics validation — NIST. In: Performance Metrics for Intelligent Systems (PerMIS 2007), December 2007

    Google Scholar 

  5. AlphaBot2 - Waveshare Wiki. https://www.waveshare.com/wiki/AlphaBot2

  6. Gazebo. http://gazebosim.org/

  7. ROS.org — Powering the world’s robots. http://www.ros.org/

  8. Costa, V., Rossetti, R.J.F., Sousa, A.: Autonomous driving simulator for educational purposes. In: 2016 11th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–5, June 2016

    Google Scholar 

  9. Roy, A., Noel, M.M.: Design of a high-speed line following robot that smoothly follows tight curves. Comput. Electr. Eng. 56, 732–747 (2016)

    Article  Google Scholar 

  10. Matczak, G., Mazurek, P.: Dim line tracking using deep learning for autonomous line following robot. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Prokopova, Z., Silhavy, P. (eds.) Artificial Intelligence Trends in Intelligent Systems. Advances in Intelligent Systems and Computing, pp. 414–423. Springer, Cham (2017)

    Google Scholar 

  11. Hassan Tanveer, M., Recchiuto, C.T., Sgorbissa, A.: Analysis of path following and obstacle avoidance for multiple wheeled robots in a shared workspace. Robotica 37(1), 80–108 (2019)

    Article  Google Scholar 

  12. Javed, M., Hamid, S., Talha, M., Ahmad, Z., Wahab, F., Ali, H.: Input based multiple destination, multiple lines following robot with obstacle bypassing. ICST Trans. Scalable Inf. Syst. 5, 154472 (2018)

    Article  Google Scholar 

  13. Ghorpade, D., Thakare, A.D., Doiphode, S.: Obstacle detection and avoidance algorithm for autonomous mobile robot using 2D LiDAR. In: 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), pp. 1–6, August 2017

    Google Scholar 

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Acknowledgements

This work is partially financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013. This research was partially supported by LIACC - Artificial Intelligence and Computer Science Laboratory of the University of Porto (FCT/UID/CEC/00027/2019).

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Correspondence to Sara Fernandes .

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Rafael, A., Santos, C., Duque, D., Fernandes, S., Sousa, A., Reis, L.P. (2020). Development of an AlphaBot2 Simulator for RPi Camera and Infrared Sensors. In: Silva, M., Luís Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_41

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