Dynamic grasping of moving objects represents one of the most challenging and actively researched areas in robotic manipulation. Unlike static grasping, this task requires the integration of perception, prediction, and control in real-time. Typical approaches involve tracking the target’s position in real-time using vision-based systems, estimating its velocity, and generating tailored Cartesian-space trajectories to ensure the robot’s end-effector coincides with the object's position at the precise time required for successful grasping. The presented work addresses the development, optimization, and hardware implementation of a novel control algorithm for dynamic grasping. The research utilizes the ROS 2 framework alongside the WidowX 250 S robotic arm, which features six degrees of freedom.