3 accepted papers
Intelligent agents use internal world models to reason and make predictions about different courses of their actions at many scales. Devising learning paradigms and architectures that allow machines to learn world models that operate at multiple levels of temporal abstractions while dealing with com…
Recently, data-driven and hybrid control of hydraulic cylinders for excavator assistance functions have been in the focus of many research papers. To ensure an accurate behavior, data-driven controllers and models need a large amount of data to cover all relevant operation regions, which requires a…
We present a comprehensive comparison of hybrid Data-Driven Control (DDC) applied on a hydraulic excavator. DDC offers a state-of-the-art, high performance control based on data and expert knowledge. On the one hand, expert knowledge is complex to adapt to each unique excavator requiring substantial…