An omni-directional kick engine for humanoid robots with parameter optimization

Incorporating a dynamic kick engine that is both fast and effective is pivotal to be competitive in one of the world’s biggest AI and robotics initiative: RoboCup. Using the NAO robot as a testbed, we developed a dynamic kick engine that can generate a kick trajectory with an arbitrary direction without prior input or knowledge of the parameters of the kick. The trajectories are generated using cubic splines (two degree three polynomials with a via-point). The trajectories are executed while the robot is dynamically balancing on one foot. When the robot swings the leg for the kick motion, unprecedented forces might be applied on the robot. To compensate for these forces, we developed a Zero Moment Point (ZMP) based preview controller that minimizes the ZMP error. Although a variety of kick engines have been implemented by others, there are only a few papers on how kick engine parameters have been optimized to give an effective kick or even a kick that minimizes energy consumption and time. Parameters such as kick configuration, limit of the robot, or shape of the polynomial can be optimized. We propose an optimization framework based on the Webots simulator to optimize these parameters. Experiments of the physical robot show promising results.