This paper presents an adaptive operation collision avoidance strategy for intelligent loaders based on high-precision LiDAR SLAM. With the advancement of automation technology, the application of intelligent loaders in complex environments such as ports is becoming increasingly widespread. The paper first analyzes how to effectively utilize point cloud data obtained from LiDAR to achieve accurate localization and mapping in feature-rich port environments. By employing a curvature-based feature extraction method to distinguish linear and planar features, the efficiency of the SLAM algorithm in processing dense feature information is improved. Furthermore, the study explores operational strategies for intelligent loaders in dynamic environments, aiming to ensure work safety through real-time collision detection and avoidance mechanisms. Experimental results demonstrate that the proposed strategy significantly enhances the operational safety and efficiency of intelligent loaders in complex port environments, providing strong support for future intelligent logistics systems.