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.
Highlights
The humanoid robot has human contour features such as limbs, head, and torso and has basic functions similar to those of human appearance
III, proposed in this article, applies all forms of motion associated with sliding in the longitudinal plane, including horizontal centroid motion, vertical centroid motion, and rotational motion at the centroid to prevent slippage and produce the desired zero moment point (ZMP)
The humanoid robot table tennis hitting movement is taken as an example, and research is carried out in the aspects of the task requirements acquisition, the whole body trajectory planning of the hitting movement, and the stability maintenance
Summary
The humanoid robot has human contour features such as limbs, head, and torso and has basic functions similar to those of human appearance. Most robotic work research such as table tennis hits mainly discusses tasks such as task target recognition and task arm trajectory planning It does not involve the full-body trajectory planning and stability control of humanoid robots. Studying the whole-body trajectory planning and stability control of humanoid robots in table tennis is a very important and effective way to improve the humanoid robot’s operating ability. This article studies the trajectory planning and balance of the whole-body coordination in the table tennis hitting movement of humanoid robots and the problem of stable control of sliding prevention. An overall trajectory planning method for humanoid table tennis batting motion is proposed, which can meet the task requirements and has the best stability. K is the drag coefficient, and g is the input in the vertical direction
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