With the continuous development of intelligent manufacturing and precision machining technology, laser processing technology has been paid more and more attention and used in industrial production. The path planning and control strategy have a decisive effect on the processing efficiency and the quality of the workpiece. However, traditional path planning methods often use the path of single-sensor data or static process parameters. Nevertheless, those are not suited to complex and dynamic past processing environments and nonlinear process behavior, which limits the rapid development of intelligent thinking systems. In this paper, the intelligent control model driven by multi-sensor data for laser path planning is proposed to achieve real-time perception, dynamic optimization, and adaptive control of the entire process of processing. In this paper, this general problem is solved with the task. First, it constructs a data acquisition system consisting of a variety of sensors, including temperature, optical power signals, visual images, and vibration sensors. Low-level fusion algorithms are proposed to solve the problem of asynchronization, noise, and multiscale characteristics by layer-by-layer, obtaining a stable high-dimensional state description. Then, the data-driven model of the fusion state creates a path with a simple model. This algorithm combines reinforcement learning and heuristic algorithms, considering the uniformity of energy and smoothness of latitude to generate the optimal track. An intelligent regulatory mechanism and an adaptive feedback control mechanism are introduced, and laser power and scanning speeds are dynamically adjusted. The simulation and real experiments verify that the proposed system is better than traditional methods for path accuracy, surface quality, and energy consumption. Multi-sensor fusion and data-driven thinking strategies as the rapid development direction of laser processing system construction are feasible. This article provides new ideas and technical support for the construction and promotion of an intelligent laser processing system.
Liu et al. (Sun,) studied this question.