Towards easier human-robot interaction to help inexperienced operators in SMEs

The capability to use advanced tools, devices, and software is essential for enterprises to survive in global competition. Inter-cognitive communication is an important element in the development of engineering applications where natural and artificial cognitive systems should work together efficiently. Small and medium-sized enterprises (SMEs) are becoming increasingly important in society, as our economies depend heavily on SMEs, which represent the majority of jobs created. Global competition has forced these SMEs to change and develop their production systems radically, to be more flexible. Industrial robots are seen as a key element in flexible manufacturing systems. However, currently, industrial robots are not commonly used in SMEs; one reason is the complex handling, especially the time-consuming programming. Industrial robot systems usually lack simple user interfaces, and the programming is usually carried out by the typical teach pendant teaching method. This method is a tedious and time-consuming task that requires a remarkable amount of expertise. In industry, this type of robot programming can be justified economically only for the production of large lot sizes, which are not typical for SMEs. Therefore, new approaches to human-robot interaction are required. Cognitive infocommunication can play a key role in these applications. Accordingly, our main goal in this paper is to present experiences in developing easier human-robot interaction to help even inexperienced operators use robots in SMEs. These examples show a variety of ways that inter-cognitive communication between human and artificial cognitive systems can be utilized in robotics. We also present our system and software architecture used in the development of generic industrial robot programming for easy-to-use applications, as well as some examples of our service robot development. Service robotics offers numerous possibilities to utilize cognitive infocommunication, but development of reli- ble and flexible solutions is challenging, due to dynamic environments, and because inexperienced users often understand very little about the robots and their internal states.