This paper assesses the efficacy of intelligent path planning for welding robots utilizing splines. Traditional path planning methods can result in inefficient and inaccurate welding operations. The study reviews current research and case studies to appraise the practical application of spline-based path planning across diverse industrial scenarios. It underscores the benefits of discovering the shortest path and reducing cycle time while acknowledging challenges such as calibration accuracy and sensitivity to sensor data noise. The introduction of artificial intelligence algorithms in automobile welding path planning enables a more precise replication of the body's design curve, ensuring the continuity and smoothness of the welding process. This, in turn, fosters further automation and optimization of the automotive welding manufacturing process. The current research concentrates on integrating intelligent optimization algorithms and spline curves to provide an efficient and intelligent method for welding path planning. Intelligent path planning based on spline curves demonstrates significant potential in enhancing welding efficiency, determining the shortest path, and holds promising applications in the broader research field of welding path planning.