Optimization and Implementation of Path Planning Algorithm for Industrial Robots for Intelligent Manufacturing

With the rapid development of intelligent manufacturing technology, the application of industrial robots in manufacturing has been gradually popularized, and their path planning ability is directly related to production efficiency and resource utilization. Traditional path planning algorithms have the problems of low efficiency and insufficient adaptability when facing the complex environmental constraints, multi-objective optimization needs and real-time response requirements in intelligent manufacturing scenarios. In this study, a hybrid collision detection algorithm is designed by integrating axis-aligned enveloping box and directed enveloping box, and based on this, a path planning optimization algorithm is designed by incorporating the artificial potential field algorithm into the fast stochastic tree-connecting algorithm, and an optimization method is proposed for the path planning of industrial robots, which focuses on the application of intelligent algorithms, the treatment of constraints, and the process of implementation of the algorithms in the actual system. . The algorithm is valuable for safety and efficiency improvement in the field of industrial automation and helps to promote the process of industrial intelligence. The significant improvement of the optimization algorithm in terms of path quality, operation efficiency and system integration is verified through performance evaluation and application examples. The research results in this paper provide technical support for efficient path planning of industrial robots in the intelligent manufacturing environment, and lay the foundation for further research and application in related fields.