RWTH Aachen

Kuz, S, Heinicke A, Schwichtenhövel D, Mayer MP, Schlick C.  2012.  The Effect of Anthropomorphic Movements of Assembly Robots on Human Prediction. Advances in Ergonomics in Manufacturing. (Karwowski, W., Trzcielinski, S., Eds.).:263-271., Boca Raton, FL: CRC Press Abstract

From a user centered point of view an important basic requirement to enable human-robot cooperation is to achieve conformity with operator's expectations of robot behavior. Therefore, this study focuses on the question, whether anthropomorphic robot movement trajectories can lead to an improved anticipation of the robot's behavior. Based on a virtual simulation environment a robotized assembly cell consisting of the assembly robot and the actual workplace was considered. In order to be able to simulate anthropomorphic movements, the human wrist trajectories of defined pick and place movements were obtained using an infrared motion capture system. The captured data were used to navigate the virtual assembly robot. Within the experiment anthropomorphic and robotic trajectories were distinguished. During the experiment, the main task of the participants was to predict the movement's destination as quickly as possible. Thus, the corresponding reaction value was analyzed to investigate the influence of anthropomorphic robot movements on human prediction in industrial environments.

Brecher, C, Breitbach T, Müller S, Mayer MP, Odenthal B, Schlick C, Herfs W.  2012.  3D Assembly Group Analysis for Cognitive Automation. Journal of Robotics. 2012(1):1-18. AbstractWebsite

A concept that allows the cognitive automation of robotic assembly processes is introduced. An assembly cell comprised of two robots was designed to verify the concept. For the purpose of validation a customer-defined part group consisting of Hubelino bricks is assembled. One of the key aspects for this process is the verification of the assembly group. Hence a software component was designed that utilizes the Microsoft Kinect to perceive both depth and color data in the assembly area. This information is used to determine the current state of the assembly group and is compared to a CAD model for validation purposes. In order to efficiently resolve erroneous situations, the results are interactively accessible to a human expert. The implications for an industrial application are demonstrated by transferring the developed concepts to an assembly scenario for switch-cabinet systems.