Automatic Decision System for the Structure of Vision-Force Robotic Control

Abstract Robotic applications are gradually taking a huge role in our everyday lives and even in the tasks which are previously thought that only human can do them. Most of these applications require robots to interact with environment, objects or even with human, which is performed by combining vision and force feedback. Generally there are five types of vision-force control: pure position control, pure force control, traded control, shared control and hybrid control. The important questions here are: How to define the most appropriate control mode for every part of different tasks and when the control system should switch from one control mode to the other. In this work an automatic decision system is suggested to define the most appropriate control mode for uncertain tasks and to choose the optimal structure of vision/force control depending on the surrounding environments and the conditions of the tasks. This research will focus on the operations of library automation as real application for the proposed control system such as sorting, storage and retrieval of imprecisely placed objects.