Kick Motions for the NAO Robot using Dynamic Movement Primitives
This work addresses motion generation for humanoid robots in soccer, but it is incremental as it applies existing DMP methods to a new domain with minor extensions.
The paper tackled the problem of generating kick motions for the NAO soccer-playing humanoid robot by applying Dynamic Movement Primitives (DMPs) for imitation and adaptation, along with a motor model to compensate for delays and maintain balance via Zero Moment Point calculation, with evaluation on real robots.
In this paper, we present the probably first application of the popular \emph{Dynamic Movement Primitives (DMP)} approach to the domain of soccer-playing humanoid robots. DMPs are known for their ability to imitate previously demonstrated motions as well as to flexibly adapt to unforeseen changes to the desired trajectory with respect to speed and direction. As demonstrated in this paper, this makes them a useful approach for describing kick motions. Furthermore, we present a mathematical motor model that compensates for the NAO robot's motor control delay as well as a novel minor extension to the DMP formulation. The motor model is used in the calculation of the Zero Moment Point (ZMP), which is needed to keep the robot in balance while kicking. All approaches have been evaluated on real NAO robots.