Development of Pid Controller Formula for Object Manipulation Using Sensor Systems
Abstract
This article reviews sensor-based vision and sensing technologies used in robotics and automated control systems for object detection and manipulation. Robotic manipulators operating in uncertain environments use a variety of sensors to ensure accuracy, reliability, and adaptability: visual sensors (cameras), force and torque sensors, rangefinders (LIDAR, ultrasound), and inertial sensors. This article analyzes inter-sensor integration, multi-sensor data processing, and algorithms for real-time object detection and manipulation. It also examines the possibilities of improving sensing systems with modern machine learning approaches.
References
1.
Islomov I.S. — Digital Image Processing and Computer Vision. Tashkent: ITM, 2020.
2.
Szeliski, R. Computer Vision: Algorithms and Applications. Springer, 2010, pp. 552-555.
3.
Dedakhanov A.O. Distribution of Moisture in the Process of Drying Cotton Raw Materials // International Scientific Research Conference, Vol. 3, 2024, No. 27, pp. 16-19.
4.
Goodfellow, I., Bengio, Y., & Courville, A. Deep Learning. MIT Press, 2016, pp. 332-336.
5.
Askarov A.A. The Role of the Fuzzy Logic Method in Detecting Fires in Production // Best Intellectual Research, 2023, Vol. 10, No. 3, pp. 126-130.
6.
Parpiyeva N. Automatic Control System of Pressing Equipment Parameters // Ethiopian International Journal of Multidisciplinary Research, 2024, Vol. 11, Issue 3, pp. 147-153.
7.
Sultonov A.M., Karimov M.M. — Fundamentals of Robotics. Tashkent: Fan va Texnologiya, 2021.
8.
Egamberdiyev M.E., Nurmatov A.B. — Automatic Control Systems and Robotics. Tashkent: ToshDTU, 2019.
9.
Akhmadaliyev Anvarbek. Neural Networks and Trees that Can Be Explained // Formation of Psychology and Pedagogy as Interdisciplinary Sciences. Italy, ISBN 978-955-3605-86-4, pp. 14-17.
10.
Axmedov R.X. — Sensors and Sensitive Elements: Theory and Practice. Tashkent: TDPU, 2022.
11.
Qo‘chqorov B.A. — Sensors and Their Application in Automation Systems. Fergana: FPI Publishing House, 2020.
12.
R.G. Rakhimov. Clean the cotton from small impurities and establish optimal parameters // The Peerian Journal. Vol. 17, pp.57-63 (2023)
13.
R.G. Rakhimov. The advantages of innovative and pedagogical approaches in the education system // Scientific-technical journal of NamIET. Vol. 5, Iss. 3, pp.293-297 (2023)
14.
F.G. Uzoqov, R.G. Rakhimov. Movement in a vibrating cotton seed sorter // DGU 22810. 03.03.2023
15.
F.G. Uzoqov, R.G. Rakhimov. The program “Creation of an online platform of food sales” // DGU 22388. 22.02.2023
16.
F.G. Uzoqov, R.G. Rakhimov. Calculation of cutting modes by milling // DGU 22812. 03.03.2023
17.
F.G. Uzoqov, R.G. Rakhimov. Determining the hardness coefficient of the sewing-knitting machine needle // DGU 23281. 15.03.2023
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.