Goller T, Völz A, Graichen K (2024)
Publication Type: Conference contribution
Publication year: 2024
Pages Range: 799-804
Event location: Newcastle upon Tyne, United Kingdom
This paper presents a programming by demonstration (PBD) approach for model predictive interaction control (MPIC). Therein, the user teaches the manipulation task including interactions multiple times. Then, the individual demonstrations are aligned using multi-dimensional dynamic time warping and modeled to retrieve nominal paths for the Cartesian pose and the interaction wrench. Based on this model, the reference profiles are segmented by a classification algorithm and a suitable parameterization of a hybrid force/motion control scheme is determined by solving an optimization problem. Finally, the overall task is saved as a sequence of manipulation primitives (MPs) and passed to the model predictive controller which is based on a path-following formulation. The effectiveness of the approach is shown by an experimental validation on a 7 degrees-of-freedom robot.
APA:
Goller, T., Völz, A., & Graichen, K. (2024). A Programming by Demonstration Approach for Robotic Manipulation with Model Predictive Interaction Control. In Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA) (pp. 799-804). Newcastle upon Tyne, United Kingdom.
MLA:
Goller, Tim, Andreas Völz, and Knut Graichen. "A Programming by Demonstration Approach for Robotic Manipulation with Model Predictive Interaction Control." Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA), Newcastle upon Tyne, United Kingdom 2024. 799-804.
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