How can I help you? An Intelligent Virtual Assistant for Industrial Robots
Chen Li, Jinha Park, Hahyeon Kim, Dimitrios Chrysostomou
Abstract
In the light of recent trends toward introducing Artificial Intelligence (AI) to enhance Human-Robot Interaction (HRI), intelligent virtual assistants (VA) driven by Natural Language Processing (NLP) receives ample attention in the manufacturing domain. However, most VAs either tightly bind with a specific robotic system or lack efficient human-robot communication. In this work, we implement a layer of interaction between the robotic system and the human operator. This interaction is achieved using a novel VA, called Max, as an intelligent and robust interface. We expand the research work in three directions. Firstly, we introduce a RESTful style Client-Server architecture for Max. Secondly, inspired by studies of human-human conversations, we embed conversation strategies into human-robot dialog policy generation to create a more natural and humanized conversation environment. Finally, we evaluate Max over multiple real-world scenarios from the exploration of an unknown environment to package delivery, with the means of an industrial robot.