Simulation-based Parameter Identification Framework for the Calibration of Rigid Body Simulation Models
Abstract
Typically, the parameter identification process for robotic systems requires a symbolic mathematical description of the inverse dynamics equation. The manual derivation of the inverse dynamics often is very time consuming and error-prone. Fortunately, modern simulation systems provide high-level interfaces for the calculation of the inverse dynamics, constituting user-friendly access to the inverse dynamics. The key idea of our research is to directly use the abstract interface of a simulation system for the parameter identification process to foster a flexible, comprehensive, application-independent parameter identification process. Applying this novel approach, the complex derivation of the inverse dynamics equation is superfluous. Instead, the inverse dynamics is described by a CAD-based simulation model and is computed by a unifying simulation algorithm. In this paper, we present the design and realization of our innovative simulation-based parameter identification framework and demonstrate the capacity of the framework by identifying the rigid body properties of the KUKA LWR4 robot.
Authors 4
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King Mongkut's University of Technology North Bangkok
Affiliation as printed
Software Systems Engineering, The Sirindhorn International Thai-German Graduate School of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
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Affiliation as printed
Institute for Man-Machine-Interaction, RWTH Aachen University, Aachen, Germany
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King Mongkut's University of Technology North Bangkok
Affiliation as printed
Software Systems Engineering, The Sirindhorn International Thai-German Graduate School of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
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Affiliation as printed
Institute for Man-Machine-Interaction, RWTH Aachen University, Aachen, Germany
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