An iterative learning control method and mathematical model for robotic manipulation at undesired locations

This paper presents an iterative learning control (ILC) strategy for a robotic manipulator when objects have to be picked up at undesired locations. The proposed ILC method can ensure that a robotic manipulator achieves its task in real time following a predetermined number of control steps. The paper has provided a robotic control strategy and mathematical formulae for the implementation of a proactive assurance control. The proactive assurance control can improve the quality of production in terms of maintaining the production workflow as a fixed value at all times, even though the components to be assembled are not in their desired locations. This can accelerate the production process owing to the possibility of eliminating the task of mounting the components at their exact locations.