Welding path planning method and system based on hybrid discrete teaching and learning optimization algorithm

Abstract

The invention discloses a welding path planning method based on a hybrid teaching and learning algorithm, and aims to improve the welding efficiency of a robot. The method comprises the following steps of: firstly, improving a teaching and learning algorithm, discretizing a traditional teaching and learning algorithm by adopting a genetic algorithm discretization method, and then expanding and optimizing the original two-stage teaching process into five stages of teacher training, teacher teaching, student learning, student self-learning and teacher reverse learning; and secondly, mixing the discretized teaching and learning optimization algorithm with a plurality of intelligent optimization algorithms, and combining the concentricity of teaching and learning optimization algorithm operators and the diversity of simulated annealing algorithm operators, so that the diversity of solutions of the hybrid teaching and learning algorithm is enhanced, the local search and global search capability of the algorithm is effectively balanced, the algorithm convergence rate is increased, and the algorithm can search an optimal path more quickly.

Description

technical field [0001] The invention belongs to the technical field of welding robot control, more specifically, a welding path planning method and system based on a hybrid discrete teaching and learning optimization algorithm. Background technique [0002] Welding robots are widely used in the field of automated manufacturing, and reasonable welding path planning helps to greatly improve welding efficiency. Therefore, the welding path planning of welding robots has become an important optimization problem in the manufacturing field, and finding an efficient method to solve this problem has high application value. [0003] Existing welding path planning methods for welding robots are mainly welding path planning methods based on Particle Swarm Optimization (PSO) and welding path planning methods based on genetic algorithms (ie, Genetic Algorithm). The former uses the neural network to train the collision penalty function to obtain a collision-free path, and then uses the pa...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a welding path planning method based on a hybrid teaching and learning algorithm. ”, and the technical problems of falling into local optimum, as well as the technical problems of poor validity and low solution accuracy of the existing welding path planning method due to limited search ability, and the existing welding path planning method is not fast enough due to the search speed. Technical issues with slow convergence and low efficiency

Images