A Machine Learning Model For Robot Kinematics And Motion Task Planning

In many industries, robots are often used for a series of repetitive tasks and then programmed to perform a different series of repetitive tasks, a process which is time consuming and expensive. In this context, the use of machine learning models to enable the robot to "learn" from its previously executed task patterns which conform to specific motion requirements can be advantageous to the industry in terms of costs and time. This paper describes a system incorporating machine learning with respect to robot kinematics and motion task planning for mechanical assembly of discrete structural parts.