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2021
Conference Paper
Titel
Empirical study for measuring the mental states of humans during the interaction with heavy-duty industrial robots
Abstract
Industrial robots are widespread in today's production facilities. However, strict safety regulations are required for their operation. Therefore, the robots usually work spatially separated from humans. Only special designs - such as lightweight robots - can currently cooperate directly with humans and actively support them. The use of lightweight robots is nowadays limited to particular assistance tasks. In the case of heavy-duty robots, certain types of cooperation become necessary, where humans and robots can mutually exploit their advantages. Beside the Safety, the human fear is another obstacle in the interaction with heavy-duty robots. The robot is a fully dynamic machine that can move in all directions. Furthermore, by implementing intelligent and autonomous robots, humans could misinterpret the movements of the robot and act in wrong way. These unforeseen movements could endanger the human. This work performs an empirical study supported by a unique platform eq uipped with various sensors and flexible fusion-tool. The objectives of this study comprise 1. Measuring the mental states of the human objectively and subjectively during the interaction with heavy-duty robots. 2. Investigating the influence of robot parameters (speed, path, interaction level etc.) and various communication systems (e.g. visual and audio systems) on the human mental states in order to reduce the negative emotions during the interaction.