Purpose The digital construction transformation requires using emerging digital technology
such as deep learning to automate implementing tasks. Therefore, this paper aims to …

The prefabricated building construction (PBC) project is sensitive to uncertainties due to the
highly required coordination and interdependency among the installation activities, which …

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 …

Accurately predicting the bucket fill rate of excavators is a challenging task due to factors
such as material flowability and the complex coupling interactions between the material 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 …

This study details an advanced shovel point optimization system for unmanned loaders,
crucial for efficient shovelling operations. First, the shovel point evaluation index is …

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 …

Effective classification and detection of equipment on construction sites is critical for efficient
equipment management. Despite substantial research efforts in this field, most previous …

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 …