Development of Smart Number Writing Robotic Arm using Stochastic Gradient Decent Algorithm
P. Velrajkumar1, C. Senthilpari2, P. Ramesh3, G. Ramanamurthy4, D. Kodandapani5
1P. Velrajkumar, Department of EEE, CMR Institute of Technology, Bengaluru, India.
2C. Senthilpari, Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia.
3P. Ramesh, Department of EEE, CMR Institute of Technology, Bengaluru, India.
4G. Ramanamurthy, Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.
5D. Kodandapani, Department of EEE, CMR Institute of Technology, Bengaluru, India.
2Dr. J.L. Narayana, Department of ECE, PSCMRECET, Vijayawada, India.
Manuscript received on 05 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 542-547 | Volume-8 Issue-10, August 2019 | Retrieval Number: J88510881019/2019©BEIESP | DOI: 10.35940/ijitee.J8851.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Robotics and Neural Networks will play a major role in the future of manufacturing and automation process. Nowadays not many robotic systems are smart systems, in the sense that they operate on a predefined algorithm to do their task. This research focuses on a design and development of a robotic arm with a visual input. The robotic arm will perform its job with the help of visual aid. The system will analyze the input image upon which the decision to write a number using Stochastic Gradient Decent (SGD) algorithm. In a nutshell this research work shows how the neural network can be incorporated with robot arm control, which is a desired field of interest in development of smart robotic systems. This work presents where the robotic arm is incorporated together with a neural network to perform a task of writing numbers using vision.
Keywords: Automation, Neural network, Robot arm, SGD, thermal vision,
Scope of the Article: Robotics Engineering