Abstract
In order to improve the planning ability of the badminton backcourt stroke line, this study designs a badminton backcourt stroke line planning method based on deep learning. Firstly, the trajectory adaptive learning method of motion primitives is used to design the hitting line nodes and path space, so as to construct the shortest distributed grid structure model of the hitting line. Then, the constraint parameters of hitting route planning are analyzed, and then the hitting position and player posture are controlled according to node positioning and shortest path optimization deployment. Finally, the adaptive optimization of the route planning process is realized by combining the deep learning method. The simulation results show that this method has good learning control ability and good convergence performance and improves the reliability of badminton backcourt hitting line planning.
Highlights
With the popularization of badminton training, higher requirements are put forward for the efficient training and pertinence of badminton. e key factor for the improvement of effects of badminton training is the badminton backcourt stroke line planning
It is necessary to build an optimized badminton backcourt stroke line planning model, combined with the optimization control method of the badminton backcourt stroke line, adopt artificial intelligence learning algorithm, realize the planning and design of the badminton backcourt stroke line, and improve the stability and reliability of the badminton backcourt stroke, and the design of the relevant badminton backcourt stroke line planning model is of great significance in guiding the optimal training ability of badminton [1]
The adaptive optimization ability of the above traditional methods for badminton backcourt stroke line planning is not good, and the spatial positioning ability is not strong. erefore, aiming at the above problems, this paper proposes a method based on deep learning for the planning of the badminton backcourt stroke route
Summary
With the popularization of badminton training, higher requirements are put forward for the efficient training and pertinence of badminton. e key factor for the improvement of effects of badminton training is the badminton backcourt stroke line planning. According to the location node distribution of the badminton backcourt stroke shown, the shortest path optimization parameter analysis model of badminton backcourt stroke line planning is constructed by using the spatial path-distributed reorganization and optimization control method. E shortest path optimization method is used to design the adaptive spatial parameters of badminton backcourt stroke line planning, and the optimal solution in the distribution nodes va, vb, and vc of the badminton backcourt stroke line is expressed as l va va + vb + vc 2 − T(t) − l vv. To sum up, taking the shortest path as the optimization objective function and using the motion primitive trajectory adaptive learning method, the badminton backcourt hitting line node and path space planning and designing are realized in the grid structure model, so as to improve the ability of route planning. According to the above analysis, the optimization parameters of badminton backcourt stroke line planning are obtained, so as to locate the nodes of the badminton backcourt stroke line and deploy the shortest path optimization
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