A Novel Self-Docking and Undocking Approach for Self-Changeable Robots

Abstract

In this paper, an efficient self-docking and self-undocking approach that can be applied to any self-changeable robot is reported. The changeable robot is a concept to extend the concept of reconfiguration in literature, and the name is first coined in this paper. The new feature of the approach is the self-search of a target module with which the remaining robot docks with and then to complete the docking. The new feature is realized by developing modules on which there are built-in cameras and distance sensors. A deep learning method based on CNN (Convolutional Neural Network) was employed to enhance the intelligence level of the docking and undocking system. The experiment was carried out to test the effectiveness of the approach based on a proprietary self-changeable robot.