Navigating Arm Robot Motion with Vision via Image Processing

Authors

  • Pola Risma Politeknik Negeri Sriwijaya
  • Tresna Dewi Politeknik Negeri Sriwijaya
  • Citra Anggraini Politeknik Negeri Sriwijaya
  • Muhammad Nawawi Politeknik Negeri Sriwijaya
  • Yurni Oktarina Politeknik Negeri Sriwijaya

DOI:

https://doi.org/10.53893/ijrvocas.v4i1.269

Keywords:

agriculture robot, arm robot manipulator, image processing, vision-based navigation

Abstract

The integration of vision-based technology in daily life has been perceived in recent years. The wide range of robot implementations, including agriculture, necessitates the installation of the eye to fully function and substitute the human eye. Camera and image processing work hand in hand in realizing the idea of automatic labor in daily life. This paper presents an arm robot navigated by image processing inputs from objects' coordinate positions. The robot is assigned to pick and place red tomatoes within different lighting and positions. The robot can sort the red tomatoes and ignore the green tomatoes. Inverse kinematics analysis is included to show the effectiveness of the proposed method. This robot is ideal for agricultural settings to sort the harvested fruit.

References

Syahrian, N. M., Risma, P., & Dewi, T. (2017). Vision-Based Pipe Monitoring Robot for Crack Detection using Canny Edge Detection Method as an Image Processing Technique, Kinetik: Game Technology, Information System, Computer Network, Computing Electronics, and Control, 2(4, 243-250. DOI: 10.22219/kinetik. v2i4.243

Dorj, U. O., Lee, M., & Yun, S. (2017). A Yield Estimation in Citrus Orchards Via Fruit Detection and Counting Using Image Processing, Computers and Electronics in Agriculture, 140, 103-112. DOI: 10.1016/j.compag.2017.05.019

Pereira, L.F.S, Barbon, S., Valous, N.A., & Barbin, D.F. (2018) Predicting the ripening of papaya fruit with digital imaging and random forests, Computers and Electronics in Agriculture, 145,76-82.https://doi.org/10.1016/j.compag.2017.12.029.

Suharjito, Elwirehardja, G. N., & Prayoga, J. S. (2021). Oil palm fresh fruit bunch ripeness classification on mobile devices using deep learning approaches, Computers and Electronics in Agriculture, 188, 106359. https://doi.org/10.1016/j.compag.2021.106359.

Zhou, W. , Cui, Y., Huang, H., & Wang, C. (2024). A fast and data-efficient deep learning framework for multi-class fruit blossom detection, Computers and Electronics in Agriculture, 217, 108592. https://doi.org/10.1016/j.compag.2023.108592.

Gill, H. S., Murugesan, G., Mehbodniya, A., Sajja, G. S., Gupta, G., & Bhatt, A., (2023). Fruit type classification using deep learning and feature fusion, Computers and Electronics in Agriculture, 211, 107990. https://doi.org/10.1016/j.compag.2023.107990.

Knott, M., Perez-Cruz, F., & Defraeye, T., (2023). Facilitated machine learning for image-based fruit quality assessment, Journal of Food Engineering, 345, 111401. https://doi.org/10.1016/j.jfoodeng.2022.111401.

Begum, N., & Hazarika, M. K. (2022). Maturity detection of tomatoes using transfer learning, Measurement: Food, 7, 100038. https://doi.org/10.1016/j.meafoo.2022.100038.

Dewi., T, Risma., P., Oktarina., Y, & Muslimin., S. (2018). Visual Servoing Design and Control for Agriculture Robot; a Review, Proc. 2019 ICECOS, 2-4 Oct. 2018, Pangkal Pinang: wIndonesia, 57-62. doi: 10.1109/ICECOS.2018.8605209.

Pal, A., Leite, A. C., From, P. J., (2024). A novel end-to-end vision-based architecture for agricultural human–robot collaboration in fruit picking operations. Robotics and Autonomous Systems, 172, 104567. https://doi.org/10.1016/j.robot.2023.104567

Ramadhan, D. I., Sari, I. P., & Sari, L. O. (2018). Comparison of Background Subtraction, Sobel, Adaptive Motion Detection, Frame Differences, and Accumulative Differences Images on Motion Detection, Sinergi, 22(1), 51-62. DOI:doi.org/10.22441/sinergi.2018.01.009

Dewi., T, Risma., P., & Oktarina., Y, (2020). Fruit Sorting Robot based on Color and Size for an Agricultural Product Packaging System, Bulletin of Electrical Engineering, and Informatics (BEEI), 9(4), 1438-1445. doi: 10.11591/eei.v9i4.2353.

Al-Shanoon, A. & Lang, H. (2022) Robotic manipulation based on 3-D visual servoing and deep neural networks, Robotics and Autonomous Systems, 152, 104041. https://doi.org/10.1016/j.robot.2022.104041.

He, Y., Gao, J., & Chen, Y., (2022). Deep learning-based pose prediction for visual servoing of robotic manipulators using image similarity, Neurocomputing, 491, 343-352. https://doi.org/10.1016/j.neucom.2022.03.045.

Tang, Y., Chen, M., Wang, C., Luo, L., Li, J., Lian, G., & Zou, X. (2020). Recognition and localization methods for vision-based fruit picking robots : A review, Frontier in Plant Science, 11, 510, 1-17. DOI: 10.3389/fpls.2020.00510

Dewi., T, Risma., P., Oktarina., Y, & Nawawi, M. "Tomato Harvesting Arm Robot Manipulator; a Pilot Project," Journal of Physics: Conference Series, 1500, p 012003, Proc. 3rd FIRST, Palembang: Indonesia, 2020, DOI: 10.1088/1742-6596/1500/1/ 012003

Bechar, A., & Vigneault, C. (2016). Agricultural robots for field operations: Concepts and components. Biosystems Engineering, 149, 94-111. https://doi.org/10.1016/j.biosystemseng.2016.06.014

Aly, B. A., Low, T., Long, D., Brett, P., & Baillie, C. (2024). Tactile sensing for tissue discrimination in robotic meat cutting: A feasibility study. Journal of Food Engineering, 363, 111754. https://doi.org/10.1016/j.jfoodeng.2023.111754

Ju, C., Kim, J., Seol, J., & Son, H. I. (2022). A review on multirobot systems in agriculture. Computers and Electronics in Agriculture, 202, 107336. https://doi.org/10.1016/j.compag.2022.107336

Aroulanandam, V. V., Satyam, Sherubha, P., Lalitha, K., Hymavathi, J., & Thiagarajan, R. (2022). Sensor data fusion for optimal robotic navigation using regression based on an IoT system. Measurement: Sensors, 24, 100598. https://doi.org/10.1016/j.measen.2022.100598

Adamides, G., Katsanos, C., Parmet, Y., Christou, G., Xenos, M., Hadzilacos, T., & Edan, Y. (2017). HRI usability evaluation of interaction modes for a teleoperated agricultural robotic sprayer. Applied Ergonomics, 62, 237-246. https://doi.org/10.1016/j.apergo.2017.03.008

Leonori, S., Mattei, S., Anniballi, L., & Frattale Mascioli, F. M. (2024). Cable-driven agribot prototype: Enabling precision agriculture through innovative design. Smart Agricultural Technology, 7, 100426. https://doi.org/10.1016/j.atech.2024.100426

Jin, T., & Han, X. (2024). Robotic arms in precision agriculture: A comprehensive review of the technologies, applications, challenges, and future prospects. Computers and Electronics in Agriculture, 221, 108938. https://doi.org/10.1016/j.compag.2024.108938

Yang, Q., Du, X., Wang, Z., Meng, Z., Ma, Z., & Zhang, Q. (2023). A review of core agricultural robot technologies for crop productions. Computers and Electronics in Agriculture, 206, 107701. https://doi.org/10.1016/j.compag.2023.107701.

Dewi., T., Nurmaini., S., Risma, P., & Oktarina., Y. (2020). Inverse Kinematic Analysis of 4 DOF Pick and Place Arm Robot Manipulator using Fuzzy Logic Controller, International Journal of Electrical and Computer Engineering (IJECE), 10(2), 1376-1386. DOI: http://doi.org/10.11591/ijece.v10i2.pp1376-138

Leanza, A., Galati, R., Ugenti, A., Cavallo, E., & Reina, G. (2023). Where am I heading? A robust approach for orientation estimation of autonomous agricultural robots. Computers and Electronics in Agriculture, 210, 107888. https://doi.org/10.1016/j.compag.2023.107888

Husaini, A. M., & Sohail, M. (2023). Robotics-assisted, organic agricultural-biotechnology based environment-friendly healthy food option: Beyond the binary of GM versus Organic crops. Journal of Biotechnology, 361, 41-48. https://doi.org/10.1016/j.jbiotec.2022.11.018

G. Feng, C. Qixin., and M. Nagata., Fruit Detachment and Classification Method for Strawberry Harvesting Robot, International Journal of Advanced Robotic Systems, 5(1), 41–48, 2018. https://doi.org/10.5772/5662.

Xiang, L., & Wang, D. (2023). A review of three-dimensional vision techniques in food and agriculture applications. Smart Agricultural Technology, 5, 100259. https://doi.org/10.1016/j.atech.2023.100259

Ren, G., Lin, T., Ying, Y., Chowdhary, G., & Ting, K. C. (2020). Agricultural robotics research applicable to poultry production: A review. Computers and Electronics in Agriculture, 169, 105216. https://doi.org/10.1016/j.compag.2020.105216

Additional Files

Published

2024-04-30

How to Cite

Risma, P., Dewi, T., Anggraini, C., Nawawi, M. ., & Oktarina, Y. (2024). Navigating Arm Robot Motion with Vision via Image Processing. International Journal of Research in Vocational Studies (IJRVOCAS), 4(1), 46–52. https://doi.org/10.53893/ijrvocas.v4i1.269