Christian Eichmann (M.Sc.)

Wissenschaftlicher Mitarbeiter

Werdegang

Christian Eichmann erwarb 2019 seinen Master of Science Informatik am Karlsruher Institut für Technologie, wobei seine Studienschwerpunkte in der Robotik und Automation lagen. Seine Abschlussarbeit "From STL to Robot Path: Generating Post-Processing Trajectories for 3D Printed Objects" verfasste er am FZI Forschungszentrum Informatik.

Seit November 2019 ist er als wissenschaftlicher Mitarbeiter in der Abteilung Interaktive Diagnose- und Servicesysteme (IDS) im Forschungsbereich Intelligent Systems and Product Engineering (ISPE) des FZI tätig.

Publikationen

Konferenzbeitrag (3)

1. Robot Health Estimation through Unsupervised Anomaly Detection using Gaussian Mixture ModelsInfoDetails

   T. Schnell and C. Plasberg and L. Puck and T. Buettner and C. Eichmann and G. Heppner and A. Roennau and R. Dillmann, 2020

   Autonomous robots in complex environments are usually forced to act very conservatively, greatly limiting their potential. Taking more risky actions confidently requires the robot to have a deep understanding of its abilities, especially in its current state. The foundation for such a self-awareness is knowledge about current damages and the stress the different components of the robot are under. While the skills of a robot can be modeled in advance, the potential errors that might occur cannot easily be predicted exhaustively. Due to this, the robot is required to notice unforeseen changes in itself and judge their severity. This work presents a solution for this in the form of a Gaussian Mixture Model based framework for anomaly detection. The model requires only training data for a healthy robot, with no samples needed for expected problems and is able to correctly notice, localize and quantity various introduced damages and impairments. Transfer to new robots requires a user to only specify available sensor data for the robot’s different components. It was implemented and tested on two different robots sharing no hardware, with different problems introduced into both systems. This approach lays the foundation for a general framework for adaptive self-aware robot decision making and planning.

2. Automation of Post-Processing in Additive Manufacturing with Industrial RobotsInfoDetails

   P. Becker and C. Eichmann and A. Roennau and R. Dillmann, 2020

   The use of industrial robots for the production of small scale manufacturing or even single pieces is rarely economical. The high investment of time and money required to teach a collision-free trajectory under consideration of all boundary conditions prevents the usage of robots until now. That is why it is still common practice in the industry for individual post-processing steps to be carried out manually, although they could be automated with today’s technical possibilities. In this paper, we present an approach on how to use existing production data (STL and G-code) to generate trajectories to automate post-processing steps. These paths can then be executed by an industrial robot, for example to post-process an additive manufactured object and remove its support structures. The object may not be damaged during the process, so all movements of the robot and its tool are checked for collisions with certain parts of the object and the environment. While material is being removed, the corresponding data structure is updated accordingly to always provide a realistic representation of the current state. This approach was evaluated by removing support structures from multiple and different-shaped objects successfully. Furthermore, we used the same approach to mill pockets in material just by changing the input data.

3. Flexible, Personal Service Robot for ALS Patients*InfoDetails

   G. P. Rivera and C. Eichmann and S. Scherzinger and L. Puck and A. Roennau and R. Dillmann, 2019

   Diseases that cause motor impairment leave people dependent on the help of caregivers or new technologies for their daily tasks. Care robots could support these patients and help them gaining autonomy in some of their daily activities. In this paper, a robotic assistant is introduced based on Amyotrophic Lateral Sclerosis patients requests for care robotics. The presented use cases are derived from their feedback and integrated using a compliant lightweight robotic arm. The system has been developed to be used independently from the input device owned by the patient, which grants an easy access to the robot without any special training. The system is flexible enough to not harm the patient for tasks that involve physical human-robot interaction, and yet precise enough to manipulate different objects. Despite the increasing acceptance of care robots in the community nowadays, the robotic assistant is one of the few robot solutions that combines autonomous behaviors and teleoperated control.

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Telefon: +49 721 9654-223
E-Mail: eichmann@dont-want-spam.fzi.de

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