Fabian Bauer

Optimierung der Energieeffizienz zweibeiniger Roboter durch elastische Kopplungen

In dieser Arbeit wird die Optimierung der Energieeffizienz zweibeiniger Roboter durch den Einsatz elastischer Kopplungen untersucht. Die betrachteten Roboter werden als unteraktuierte Systeme modelliert und mittels Ein-Ausgangs-Linearisierung geregelt. Zur Untersuchung des Einflusses der elastischen Kopplungen auf Energieeffizienz sowie Stabilitat und Robustheit werden parallel die Bewegungen der Roboter als auch deren elastische Kopplungen unter Anwendung numerischer Algorithmen optimiert.

Stability and Robustness of a 3D Slip Model for Walking Using Lateral Leg Placement Control

The SLIP model has shown a way to easily represent the center of mass dynamics of human walking and running. For 2D motions in the sagittal plane, the model shows self-stabilizing effects that can be very useful when designing a humanoid robot. However, this self-stability could not be found in three-dimensional running, but simple control strategies achieved stabilization of running in three dimensions. Yet, 3D walking with SLIP has not been analyzed to the same extent. In this paper we show that three-dimensional humanoid SLIP walking is also unstable, but can be stabilized using the same strategy that has been successful for running. It is shown that this approach leads to the desired periodic solutions. Furthermore, the influence of different parameters on stability and robustness is examined. Using a performance test to simulate the transition from an upright position to periodic walking we show that the stability is robust. With a comparison of common models for humanoid walking and running it is shown that the simple control mechanism is able to achieve stable solutions for all models, providing a very general approach to this problem. The derived results point out preferable parameters to increase robustness promising the possibility of successfully realizing a humanoid walking robot based on 3D SLIP.Copyright

Determining the principles of human motion by combining motion analysis and motion synthesis

Synthesizing of human motion is one of the challenges in humanoid robotics research. Interested in the construction of humanoid service robots exhibiting human-like movements research is following different ways. This paper is going along with the idea of determining the principles of human motor control in order to understand the generation of human motion. A computational framework based on an efficient technique combining motion capture with multibody systems and optimal control theory for large-scale dynamic analysis and synthesis of motion is presented. Experiments were performed for human pointing gestures and the framework was validated computing the optimal trajectories of minimum hand jerk, modified minimum hand jerk, minimum angle jerk and minimum torque change.