Research on sports planning and stability control of humanoid robot table tennis

Abstract

The humanoid robot has the human shape and has great advantages in assisting human life and work. The ability to work, especially in a dynamic, unstructured environment, is an important prerequisite for humanoid robots to assist humans in their mission. Table tennis hitting involves a variety of key technologies such as visual inspection, trajectory planning, and artificial intelligence. It is an important research example that can reflect the ability of humanoid robots. First, according to the requirements of humanoid robots in the human living environment and the requirements of coordinating table tennis batting movements throughout the body, a method of establishing a humanoid robot model was analyzed, and a control system was designed to meet the needs of rapid table tennis batting. Second, a motion model construction and optimization algorithm based on intelligent learning training is proposed. Based on the parameter knowledge base established by the multiple trajectories of table tennis, a kind of electromagnetic mechanism and D-optimality regularized orthogonal minima are introduced. Design a two-pass method (regularized orthogonal least squares method + D-optimality) to learn the two-level learning method, which is used to learn the key parameters of the table tennis model. Third, for human-like robotic table tennis fast-moving, it is necessary to satisfy both the task and the stability requirements and to propose a stability-optimized whole-system coordinated trajectory planning method. The effectiveness of the proposed humanoid robot table tennis hitting motion planning and stability control method is verified by experiments.