Construction machinery and robots are essential equipment for major infrastructure. The
application of deep learning technology can improve the construction quality and alleviate …

Along with the rapid development of infrastructure worldwide, traditional manual operations
have been a concern that restricts the high efficiency, safety, and quality of construction …

Time Series Classification (TSC) problems are encountered in many real life data mining
tasks ranging from medicine and security to human activity recognition and food safety. With …

Automation of earth-moving industries (construction, mining and quarry) require automatic
bucket-filling algorithms for efficient operation of front-end loaders. Autonomous bucket …

Earth-moving machines are heavy-duty vehicles designed for construction operations
involving earthworks. The tasks performed by such machines typically involve navigation …

The bucket motion of a wheel loader during the loading process is investigated in this study.
The optimal bucket loading trajectory can be obtained by solving an optimal control problem …

Bucket-filling is a repetitive task in earth-moving operations with wheel-loaders, which needs
to be automated to enable efficient remote control and autonomous operation. Ideally, an …

This paper presents a robust machine learning framework for modeling and control of
hydraulic actuators. We identify several important challenges concerning learning accurate …

This study introduces expedite the complete transfer of distributed gravel piles with an
automated wheel loader. The wheel loader scoops the gravel and unloads it onto the bed of …

In the automatic shoveling operation of wheel loaders, the shovel trajectory has a significant
influence on the operation's performance. In order to obtain a suitable shovel trajectory and …