The work discusses the semi-autonomous operations of a truck-mounted concrete pump, specifically focusing on its setup process at construction sites. This involves stabilizing the machine with support feet and unfolding the concrete distribution boom.
To tackle these issues, practical assistance systems are developed, using tailored mathematical models derived from physical principles to aid operators. These models are calibrated with real-world machine measurements, ensuring accurate motion representation in simulations. Leveraging these models, customized planning tools are created for machine motions, executed and stabilized using established automation and control techniques.
For supporting the machine, an exhaustive simulation analysis is conducted, resolving the question of achieving maximal stable support. Insights gained lead to a computationally efficient planning and control algorithm developed for practical use.
Developing an optimization-based motion planning system for boom unfolding and folding considers various constraints (technical and legal), notably collision avoidance within the workspace. An algorithm prioritizing robustness and computational efficiency is presented, leveraging system geometry to simplify complexity. An alternative motion planning strategy for the concrete distribution task based on desired Cartesian paths is also introduced.
Extensive simulation studies validate proposed concepts, particularly the boom unfolding planning and stabilization algorithm through real-world measurements.
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Research Areas:
Mathematical and Algorithmic Foundations: 60% Modeling and Simulation: 40%
