A Machine Learning Methodology for Classification of Movement Articulation For Robotics
L.Jagajeevan Rao1, Ram Kumar Madupu2, CMAK Zeelan Basha3
1L.Jagajeevan Rao , Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
2Ram kumar Madupu Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
3CMAK Zeelan Basha, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12327-12330 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8508118419/2019©BEIESP | DOI: 10.35940/ijrte.D8508.118419
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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: Communication one another through target-arranged methodologies have been usually utilized in mechanical technology. Development of an automated arm can include focusing on by means of a forward or backwards kinematics way reach the target. We endeavored to change the assignment of controlling the controlling the motor to an AI approach. Though we have many machine learning approaches we implemented an online automated arm to separate verbalization datasets and have utilized BPNN and ANN methods to foresee multijoint explanation. For improving the accuracy,we created pick and spot assignments dependent on pre-stamped positions and removed preparing datasets which were then utilized for learning. We have utilized classification instead of prediction-correction approach which usually attempted in traditional robotics. This investigation reports noteworthy grouping precision and effectiveness on genuine and engineered datasets created by the gadget. The examination significant classification accuracy and efficiency BPNN and ANN calculations as alternatives for computational concentrated forecast remedy learning plans for articulator development in lab environments.
Keywords: Machine learning, BPNN, ANN, Robtics, AI
Scope of the Article: Machine Learning.