Abstract
Robots have been playing a very important role in our day-to-day lives and will be a necessity in the coming future. Whenever we hear automation, the first thing that strikes our mind is a robot performing the given task. But if a robot fails to do the task, it could cost an individual or corporate a huge financial loss. In this study, we have learned the working of various robots and drawbacks that hold them back. For this work, we did make a study of drives used in the robot and after that applied the machine learning algorithms to predict the classification of whether the robot will function properly or not, based on the data of drive(s).
Highlights
Robots now-a-days have witnessed a large number of users since the process of automation hasbegun
The question arises do we know will the robot perform the given task accurately or even if it does it accurately, does it do it the right way. To overcome such difficulties and ease the human decision making for assigning task to robot, we need algorithms to predict the result of robot[1], using its dynamic dataset which is integrated with the cloud[2]
The system is based on drive predictions on the features and data generated by each drive of the robot as an input to the system
Summary
Robots now-a-days have witnessed a large number of users since the process of automation hasbegun. The question arises do we know will the robot perform the given task accurately or even if it does it accurately, does it do it the right way. To overcome such difficulties and ease the human decision making for assigning task to robot, we need algorithms to predict the result of robot[1], using its dynamic dataset which is integrated with the cloud[2]. The objective of this workis predictive maintenance of industrial robots and the possibility of building a condition monitoring system based on the data analysis of the robot’s locomotion which brings the work of individuals at one place.The aim of this study is to detect the robot’s accuracy for performing a task correctly.This can be checked by observing a robot for a certain period and using that dataset for prediction[3]
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