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Adrian Trachte

2 accepted papers

2023

Safe Active Learning and Probabilistic Design of Experiment for Autonomous Hydraulic Excavators

IROS 2023poster

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…

Cited by 1SourceScholar
2021

Hybrid Data-Driven Modelling for Inverse Control of Hydraulic Excavators

IROS 2021poster

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…

Cited by 10SourceScholar