Path optimization for abstractly represented tasks with respect to efficient control

In order to be able to replace a human operator, a robotic manipulation system needs to deal with a variety of possible actions. These actions may be more or less constrained in their motion profile and in the accuracy of the transport goals. The robotic system can make use of some of this variation to simplify the control to improve the efficiency of the generated motion. Nevertheless, the human´s intention behind the manipulation may not change. We introduce the Elastic Power Path to optimize paths with respect to efficient control in the context of abstractly represented tasks. Our experiments show, that the proposed Elastic Power Path is an efficient method to achieve this aim. The magnitude and the number of turnarounds of the accelerations along the path are significantly reduced.