This study aims to solve the problem of material detection and shovel difficulty judgment of
earth moving machinery and characterize the material shovel difficulty by using radar chart …

Excavators are crucial in the construction industry, and develo** autonomous excavator
systems is vital for enhancing productivity and reducing the reliance on manual labor …

In earthmoving equipment, overloading and underloading transport vehicles reduce the
production efficiency. This paper presents a novel online loader payload prediction method …

Aircraft bearings are the supporting part of aeroengines, so their stable operation
guarantees engine safety. At present, multisensor information fusion is very common in the …

Highlights•In-situ LiDAR grain surface height map** system developed.•Developed a dust
filtering algorithm to reduce LiDAR sensor noise.•Grain level stereo camera-based …

Automated monitoring of bulldozer operation cycles is crucial for efficient productivity
assessment and precise construction management. Harsh earthwork environments and …

This paper introduces a bucket fill factor estimation method for earthmoving machinery
aimed at solving sensor field-of-view blindness in measurements. Utilizing a point cloud …

The need for high productivity in the construction field is becoming increasingly urgent, and
the efficiency of loading and unloading materials by construction vehicles is one of the main …

The bucket fill factor is a core evaluation indicator for the optimization of the loader's
autonomous shoveling operation. Accurately predicting the bucket fill factor of the loader …

The development of autonomous detection technology is imperative in the field of
construction. The bucket fill factor is one of the main indicators for evaluating the productivity …