فهرست نشریات علمی دسترسی آزاد ایران

Advancements in excavator technology play a critical role in improving safety, and productivity in nonmetallic material extraction. This study investigated the rational placement of LiDAR sensors on excavators to improve hazard detection and operational stability. The proposed method integrates side- and top-mounted LiDAR sensors to identify hazards, classify objects, and secure excavator positioning on sloped terrain. Advanced data processing techniques, including ground plane removal, region-of-interest restriction, and dynamic object detection, were implemented to improve hazard identification. A custom algorithm was developed to process the LiDAR data, filter irrelevant objects, and provide real-time recommendations for improving excavator stability. The results indicate that the system achieved a 95% hazard detection accuracy in high-risk zones with a radius of (0-5 m), reduced positioning errors by 20%, and reduced the excavation cycle time by 10-15%. The findings suggest that side-mounted LiDAR placement offers superior detection capabilities and stability benefits compared with top-mounted configurations. The integration of 3D LiDAR with AI-driven analytics enables more precise depth perception, obstacle recognition, and adaptive positioning, thereby significantly enhancing operational accuracy.