Research Article
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The SMaRt: Design, implementation, and experiment

Year 2023, , 214 - 223, 31.12.2023

Ahmet Top , Gökhan Güngör , Muammer Gökbulut

https://doi.org/10.36222/ejt.1340895

Abstract

Mobile robots, for teaching and research activities, have an important place in all education levels, from higher to primary education. They provide a malleable platform to meet research and teaching needs in various engineering and science fields, such as mechanics, electronics, software, biology, and psychology. However, their high cost and the difficulty of learning the user interface and programming tools prevent the widespread use of mobile robots. In this study, we develop an affordable, symmetric, modular, interactive, human-aware, autonomous, and four-wheel-driven mobile robot to boost the quality of education and research. The proposed mobile system is fully customizable with open hardware, software, and data to meet the unique demands and specifications of teaching and research. The developed mobile robot has been successfully operated for education and research purposes.

Keywords

Mobile robot control Motion planning İmage processing Teaching Education

Project Number

TEKF.19.07

References

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  • [2] Felicia A, Sharif S. A review on educational robotics as assistive tools for learning mathematics and science. Int. J. Comput. Sci. Trends Technol, vol. 2, no. 2, pp. 62–84, 2014.
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  • [4] Merdan, M, Lepuschitz, W, Koppensteiner, G, & Balogh R. Balogh, Robotics in education: Research and practices for robotics in STEM education, vol. 457. Springer, 2016.
  • [5] Eguchi, A. Robocup junior for promoting stem education, 21st-century skills, and technological advancement through robotics competition. Robotics and Autonomous Systems, vol. 75, pp. 692–699, 2016.
  • [6] Curto B, Moreno V. Robotics in education. Journal of Intelligent & Robotic Systems, vol. 81, no. 1, p. 3, 2016.
  • [7] Lindsay S, and Hounsell KG. Adapting a robotics program to enhance participation and interest in stem among children with disabilities: a pilot study. Disability and Rehabilitation: Assistive Technology, vol. 12, no. 7, pp. 694–704, 2017.
  • [8] Rivera JH. Science-based laboratory comprehension: an examination of effective practices within traditional, online and blended learning environments. Open Learning: The Journal of Open, Distance and e- Learning, vol. 31, no. 3, pp. 209–218, 2016.
  • [9] Felder RM, Soloman BA et al. Learning styles and strategies. 2000
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  • [12] Spolaor, N., & Benitti, F. B. V. Robotics applications grounded in learning theories on tertiary education: A systematic review. Computers & Education, vol. 112, pp. 97–107, 2017.
  • [13] Giang, C., Piatti, A., & Mondada, F. Heuristics for the development and evaluation of educational robotics systems. IEEE Transactions on Education, vol. 62, no. 4, pp. 278–287, 2019.
  • [14] Ceccarelli M. Robotic teachers’ assistants. IEEE Robotics & Automation Magazine, vol. 10, no. 3, pp. 37–45, 2003.
  • [15] Piepmeier, J. A., Bishop, B. E., & Knowles, K. A. Modern robotics engineering instruction. IEEE Robotics & Automation Magazine, vol. 10, no. 2, pp. 33–37, 2003.
  • [16] Robinette M.F, Manseur R. Robot-draw, an internet-based visualization tool for robotics education. IEEE Transactions on Education, vol. 44, no. 1, pp. 29–34, 2001.
  • [17] Nagai K. Learning while doing: practical robotics education. IEEE Robotics & Automation Magazine, vol. 8, no. 2, pp. 39–43, 2001.
  • [18] Wu, M., She, J. H., Zeng, G. X., & Ohyama, Y. Internet-based teaching and experiment system for control engineering course. IEEE Transactions on Industrial Electronics, vol. 55, no. 6, pp. 2386–2396, 2008.
  • [19] Gardun˜o-Aparicio, M., Rodr´ıguez-Res´endiz, J., Macias-Bobadilla, G., & Thenozhi, S. A multidisciplinary industrial robot approach for teaching mechatronics-related courses. IEEE Transactions on Education, vol. 61, no. 1, pp. 55–62, 2017.
  • [20] Nao the humanoid and programmable robot. [Online]. Website https://www.softbankrobotics.com/emea/en/nao
  • [21] Giovannangeli C, and Gaussier P. Interactive teaching for visionbased mobile robots: A sensory-motor approach. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 40, no. 1, pp. 13–28, 2009.
  • [22] Jojoa, E. M. J., Bravo, E. C., & Cortes, E.B.B. Tool for experimenting with concepts of mobile robotics as applied to children’s education. IEEE Transactions on Education, vol. 53, DOI 10.1109/TE.2009.2024689, no. 1, pp. 88–95, 2010.
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  • [26] Cianci, C. M., Raemy, X., Pugh, J., & Martinoli, A. Communication in a swarm of miniature robots: The e-puck as an educational tool for swarm robotics. in International Workshop on Swarm Robotics, pp. 103–115. Springer, 2006.
  • [27] Francesca, G., Brambilla, M., Brutschy, A., Trianni, V., & Birattari, M. Automode: A novel approach to the automatic design of control software for robot swarms. Swarm Intelligence, vol. 8, no. 2, pp. 89– 112, 2014.
  • [28] Prieto, A., Becerra, J. A., Bellas, F., & Duro, R. J. Open-ended evolution as a means to self-organize heterogeneous multi-robot systems in real-time. Robotics and Autonomous Systems, vol. 58, no. 12, pp. 1282– 1291, 2010.
  • [29] Greenwald L, Kopena J. Mobile robot labs. IEEE Robotics & Automation Magazine, vol. 10, no. 2, pp. 25–32, 2003.
  • [30] G´omez-de-Gabriel, J. M., Mandow, A., Fernandez-Lozano, J., & Garcia-Cerezo, A. Mobile robot lab project to introduce engineering.
  • [31] Scribbler 3 (s3) robot. [Online]. Website https://www.parallax.com/ product/scribbler-3-s3-robot students to fault diagnosis in mechatronic systems,” IEEE Transactions on Education, vol. 58, no. 3, pp. 187–193, 2014. [accessed 7 May 2023].
  • [32] Calvo, I., Cabanes, I., Quesada, J., & Barambones, O. A multidisciplinary pbl approach for teaching industrial informatics and robotics in engineering. IEEE Transactions on Education, vol. 61, no. 1, pp. 21–28, 2017.
  • [33] Do Y. Self-selective multi-objective robot vision projects for students of different capabilities. Mechatronics, vol. 23, no. 8, pp. 974–986, 2013.
  • [34] Quanser qbot 3. [Online]. Website https://www.quanser.com/products/ qbot-3/ [accessed 12 May 2023].
  • [35] Pioneer 3-dx robot. [Online].Website https://www.generationrobots. com/media/Pioneer3DX-P3DX-RevA.pdf [accessed 12 May 2023].
  • [36] Turtlebot 2 robot. [Online].Website https://clearpathrobotics.com/ turtlebot-2-open-source-robot [accessed 12 May 2023].
  • [37] Gritti, A. P., Tarabini, O., Guzzi, J., Di Caro, G. A., Caglioti, V., Gambardella, L. M., & Giusti, A. Kinect-based people detection and tracking from small-footprint ground robots. in International Conference on Intelligent Robots and Systems (IROS), pp. 4096–4103, 2014.
  • [38] Wu, K., Ranasinghe, R., & Dissanayake, G. Active recognition and pose estimation of household objects in clutter. in International Conference on Robotics and Automation (ICRA), pp. 4230–4237. IEEE, 2015.
  • [39] Barber, R., Rodriguez-Conejo, M. A., Melendez, J., & Garrido, S. Design of an infrared imaging system for robotic inspection of gas leaks in industrial environments. International Journal of Advanced Robotic Systems, vol. 12, no. 3, p. 23, 2015.
  • [40] Turtlebot 3 robot. [Online].Website https://emanual.robotis.com/docs/ en/platform/turtlebot3/overview [accessed 15 May 2023].
  • [41] Amsters R. and Slaets P. Turtlebot 3 as a robotics education platform. in International Conference on Robotics in Education (RiE), pp. 170– 181. Springer, 2019.
  • [42] Turtlebot 4 robot. [Online]. Website https://clearpathrobotics.com/ turtlebot-4 [accessed 15 May 2023].
  • [43] Microcontroller. [Online]. Website https: //ww1.microchip. com/ downloads/en/devicedoc/ atmel-11057-32-bit- cortex-m3-micro contr oller-sam3x-sam3a datasheet.pdf [accessed 15 May 2023].
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  • [45] Lattepanda. [Online]. Website https://www.lattepanda.com [accessed 17 May 2023].
  • [46] Raspberry pi 4. [Online].Website https://www.raspberrypi.com/ products/raspberry-pi-4-model-b [accessed 17May 2023].
  • [47] Nvidia jetson nano developer kit. [Online].Website https://developer. nvidia.com/embedded/jetson-nano-developer- kit [accessed 17 May 2023].
  • [48] Dc motor. [Online]. Website https://www.pololu.com/product/4756/ specs [accessed 17 May 2023].
  • [49] Sparkfun monster moto shield. [Online]. Website https://www.sparkfun.com/products/retired/10182 [accessed 17 May 2023].
  • [50] Sharp infrared distance measuring sensor. [Online]. Website https: //www.sparkfun.com/datasheets/Sensors/ In- frared/gp2y0a02yk e.pdf [accessed 17 May 2023].
  • [51] Ultrasonic distance sensor - hc-sr04. [Online]. Website https: //www.sparkfun.com/products/15569 [accessed 17 May 2023].
  • [52] Zed 1 stereo camera. [Online]. Website https://www.stereolabs.com/ zed-1 [accessed 17 May 2023].
  • [53] Slamtec rplidar-a3 laser range scanner. [Online]. Website https: //www.slamtec.com/en/Lidar/A3 [accessed 17 May 2023].
  • [54] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. You only look once: Unified, real-time object detection. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 779–788, 2016.
  • [55] Top, A., & Go¨kbulut, M. Android application design with mit app inventor for bluetooth based mobile robot control. Wireless Personal Communications, pp. 1–27, 2022.

Year 2023, , 214 - 223, 31.12.2023

Ahmet Top , Gökhan Güngör , Muammer Gökbulut

https://doi.org/10.36222/ejt.1340895

Abstract

Supporting Institution

Fırat Üniversitesi

Project Number

TEKF.19.07

References

  • [1] Calo R. The case for a federal robotics commission. Available at SSRN 2529151, 2014.
  • [2] Felicia A, Sharif S. A review on educational robotics as assistive tools for learning mathematics and science. Int. J. Comput. Sci. Trends Technol, vol. 2, no. 2, pp. 62–84, 2014.
  • [3] Khine, M. S., Khine, M. S., & Ohmer. Robotics in STEM Education. Springer, 2017.
  • [4] Merdan, M, Lepuschitz, W, Koppensteiner, G, & Balogh R. Balogh, Robotics in education: Research and practices for robotics in STEM education, vol. 457. Springer, 2016.
  • [5] Eguchi, A. Robocup junior for promoting stem education, 21st-century skills, and technological advancement through robotics competition. Robotics and Autonomous Systems, vol. 75, pp. 692–699, 2016.
  • [6] Curto B, Moreno V. Robotics in education. Journal of Intelligent & Robotic Systems, vol. 81, no. 1, p. 3, 2016.
  • [7] Lindsay S, and Hounsell KG. Adapting a robotics program to enhance participation and interest in stem among children with disabilities: a pilot study. Disability and Rehabilitation: Assistive Technology, vol. 12, no. 7, pp. 694–704, 2017.
  • [8] Rivera JH. Science-based laboratory comprehension: an examination of effective practices within traditional, online and blended learning environments. Open Learning: The Journal of Open, Distance and e- Learning, vol. 31, no. 3, pp. 209–218, 2016.
  • [9] Felder RM, Soloman BA et al. Learning styles and strategies. 2000
  • [10] Nguyen, K. A., DeMonbrun, R. M., Borrego, M. J., Prince, M. J., Husman, J., Finelli, C. J., ... & Waters, C. The variation of nontraditional teaching methods across 17 undergraduate engineering classrooms. in 2017 ASEE Annual Conference & Exposition, 2017.
  • [11] Hernandez-de-Menendez, M., Escobar D´ıaz, C., & Morales-Menendez, R. Technologies for the future of learning: state of the art. International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 14, no. 2, pp. 683–695, 2020.
  • [12] Spolaor, N., & Benitti, F. B. V. Robotics applications grounded in learning theories on tertiary education: A systematic review. Computers & Education, vol. 112, pp. 97–107, 2017.
  • [13] Giang, C., Piatti, A., & Mondada, F. Heuristics for the development and evaluation of educational robotics systems. IEEE Transactions on Education, vol. 62, no. 4, pp. 278–287, 2019.
  • [14] Ceccarelli M. Robotic teachers’ assistants. IEEE Robotics & Automation Magazine, vol. 10, no. 3, pp. 37–45, 2003.
  • [15] Piepmeier, J. A., Bishop, B. E., & Knowles, K. A. Modern robotics engineering instruction. IEEE Robotics & Automation Magazine, vol. 10, no. 2, pp. 33–37, 2003.
  • [16] Robinette M.F, Manseur R. Robot-draw, an internet-based visualization tool for robotics education. IEEE Transactions on Education, vol. 44, no. 1, pp. 29–34, 2001.
  • [17] Nagai K. Learning while doing: practical robotics education. IEEE Robotics & Automation Magazine, vol. 8, no. 2, pp. 39–43, 2001.
  • [18] Wu, M., She, J. H., Zeng, G. X., & Ohyama, Y. Internet-based teaching and experiment system for control engineering course. IEEE Transactions on Industrial Electronics, vol. 55, no. 6, pp. 2386–2396, 2008.
  • [19] Gardun˜o-Aparicio, M., Rodr´ıguez-Res´endiz, J., Macias-Bobadilla, G., & Thenozhi, S. A multidisciplinary industrial robot approach for teaching mechatronics-related courses. IEEE Transactions on Education, vol. 61, no. 1, pp. 55–62, 2017.
  • [20] Nao the humanoid and programmable robot. [Online]. Website https://www.softbankrobotics.com/emea/en/nao
  • [21] Giovannangeli C, and Gaussier P. Interactive teaching for visionbased mobile robots: A sensory-motor approach. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 40, no. 1, pp. 13–28, 2009.
  • [22] Jojoa, E. M. J., Bravo, E. C., & Cortes, E.B.B. Tool for experimenting with concepts of mobile robotics as applied to children’s education. IEEE Transactions on Education, vol. 53, DOI 10.1109/TE.2009.2024689, no. 1, pp. 88–95, 2010.
  • [23] Arvin, F., Espinosa, J., Bird, B., West, A., Watson, S., & Lennox, B. Mona: an affordable open-source mobile robot for education and research. Journal of Intelligent & Robotic Systems, vol. 94, no. 3, pp. 761–775, 2019.
  • [24] Maxwell B.A, and Meeden L.A. Integrating robotics research with undergraduate education. IEEE Intelligent systems and their applications, vol. 15, no. 6, pp. 22–27, 2000.
  • [25] Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., ... & Martinoli, A. The epuck, a robot designed for education in engineering. in Proc. of the 9th conference on autonomous robot systems and competitions, vol. 1, no. CONF, pp. 59–65. IPCB: Instituto Polit´ecnico de Castelo Branco, 2009.
  • [26] Cianci, C. M., Raemy, X., Pugh, J., & Martinoli, A. Communication in a swarm of miniature robots: The e-puck as an educational tool for swarm robotics. in International Workshop on Swarm Robotics, pp. 103–115. Springer, 2006.
  • [27] Francesca, G., Brambilla, M., Brutschy, A., Trianni, V., & Birattari, M. Automode: A novel approach to the automatic design of control software for robot swarms. Swarm Intelligence, vol. 8, no. 2, pp. 89– 112, 2014.
  • [28] Prieto, A., Becerra, J. A., Bellas, F., & Duro, R. J. Open-ended evolution as a means to self-organize heterogeneous multi-robot systems in real-time. Robotics and Autonomous Systems, vol. 58, no. 12, pp. 1282– 1291, 2010.
  • [29] Greenwald L, Kopena J. Mobile robot labs. IEEE Robotics & Automation Magazine, vol. 10, no. 2, pp. 25–32, 2003.
  • [30] G´omez-de-Gabriel, J. M., Mandow, A., Fernandez-Lozano, J., & Garcia-Cerezo, A. Mobile robot lab project to introduce engineering.
  • [31] Scribbler 3 (s3) robot. [Online]. Website https://www.parallax.com/ product/scribbler-3-s3-robot students to fault diagnosis in mechatronic systems,” IEEE Transactions on Education, vol. 58, no. 3, pp. 187–193, 2014. [accessed 7 May 2023].
  • [32] Calvo, I., Cabanes, I., Quesada, J., & Barambones, O. A multidisciplinary pbl approach for teaching industrial informatics and robotics in engineering. IEEE Transactions on Education, vol. 61, no. 1, pp. 21–28, 2017.
  • [33] Do Y. Self-selective multi-objective robot vision projects for students of different capabilities. Mechatronics, vol. 23, no. 8, pp. 974–986, 2013.
  • [34] Quanser qbot 3. [Online]. Website https://www.quanser.com/products/ qbot-3/ [accessed 12 May 2023].
  • [35] Pioneer 3-dx robot. [Online].Website https://www.generationrobots. com/media/Pioneer3DX-P3DX-RevA.pdf [accessed 12 May 2023].
  • [36] Turtlebot 2 robot. [Online].Website https://clearpathrobotics.com/ turtlebot-2-open-source-robot [accessed 12 May 2023].
  • [37] Gritti, A. P., Tarabini, O., Guzzi, J., Di Caro, G. A., Caglioti, V., Gambardella, L. M., & Giusti, A. Kinect-based people detection and tracking from small-footprint ground robots. in International Conference on Intelligent Robots and Systems (IROS), pp. 4096–4103, 2014.
  • [38] Wu, K., Ranasinghe, R., & Dissanayake, G. Active recognition and pose estimation of household objects in clutter. in International Conference on Robotics and Automation (ICRA), pp. 4230–4237. IEEE, 2015.
  • [39] Barber, R., Rodriguez-Conejo, M. A., Melendez, J., & Garrido, S. Design of an infrared imaging system for robotic inspection of gas leaks in industrial environments. International Journal of Advanced Robotic Systems, vol. 12, no. 3, p. 23, 2015.
  • [40] Turtlebot 3 robot. [Online].Website https://emanual.robotis.com/docs/ en/platform/turtlebot3/overview [accessed 15 May 2023].
  • [41] Amsters R. and Slaets P. Turtlebot 3 as a robotics education platform. in International Conference on Robotics in Education (RiE), pp. 170– 181. Springer, 2019.
  • [42] Turtlebot 4 robot. [Online]. Website https://clearpathrobotics.com/ turtlebot-4 [accessed 15 May 2023].
  • [43] Microcontroller. [Online]. Website https: //ww1.microchip. com/ downloads/en/devicedoc/ atmel-11057-32-bit- cortex-m3-micro contr oller-sam3x-sam3a datasheet.pdf [accessed 15 May 2023].
  • [44] Arduino due. [Online]. Website https://store.arduino.cc/products/ arduino-due [accessed 15 May 2023].
  • [45] Lattepanda. [Online]. Website https://www.lattepanda.com [accessed 17 May 2023].
  • [46] Raspberry pi 4. [Online].Website https://www.raspberrypi.com/ products/raspberry-pi-4-model-b [accessed 17May 2023].
  • [47] Nvidia jetson nano developer kit. [Online].Website https://developer. nvidia.com/embedded/jetson-nano-developer- kit [accessed 17 May 2023].
  • [48] Dc motor. [Online]. Website https://www.pololu.com/product/4756/ specs [accessed 17 May 2023].
  • [49] Sparkfun monster moto shield. [Online]. Website https://www.sparkfun.com/products/retired/10182 [accessed 17 May 2023].
  • [50] Sharp infrared distance measuring sensor. [Online]. Website https: //www.sparkfun.com/datasheets/Sensors/ In- frared/gp2y0a02yk e.pdf [accessed 17 May 2023].
  • [51] Ultrasonic distance sensor - hc-sr04. [Online]. Website https: //www.sparkfun.com/products/15569 [accessed 17 May 2023].
  • [52] Zed 1 stereo camera. [Online]. Website https://www.stereolabs.com/ zed-1 [accessed 17 May 2023].
  • [53] Slamtec rplidar-a3 laser range scanner. [Online]. Website https: //www.slamtec.com/en/Lidar/A3 [accessed 17 May 2023].
  • [54] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. You only look once: Unified, real-time object detection. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 779–788, 2016.
  • [55] Top, A., & Go¨kbulut, M. Android application design with mit app inventor for bluetooth based mobile robot control. Wireless Personal Communications, pp. 1–27, 2022.
There are 55 citations in total.

Details

Primary Language English
Subjects Electrical Engineering (Other)
Journal Section Research Article
Authors

Ahmet Top 0000-0001-6672-2119

Gökhan Güngör 0000-0003-0666-3158

Muammer Gökbulut 0000-0003-1870-1772

Project Number TEKF.19.07
Publication Date December 31, 2023
Published in Issue Year 2023

Cite

APA Top, A., Güngör, G., & Gökbulut, M. (2023). The SMaRt: Design, implementation, and experiment. European Journal of Technique (EJT), 13(2), 214-223. https://doi.org/10.36222/ejt.1340895

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