Gold T, Lomakin A, Goller T, Völz A, Graichen K (2020)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2020
Pages Range: 401 - 407
DOI: 10.1109/icma49215.2020.9233628
This paper presents an optimization-based control framework for robotic manipulation tasks. A hierarchical and systematic decomposition is used in order to formulate the high-level task as a sequence of manipulation primitives. A key difficulty is that different primitives usually require different strategies to control motions and forces. However, based on the concept of model predictive interaction control (MPIC), it is possible to use the same control approach for all primitives. Instead of changing the controller, only the parameterization of the MPIC, i.e. the cost function and the constraints, is adapted for each primitive. The hierarchical task decomposition and the generic control concept are demonstrated for a screwing application using a robot arm with seven degrees of freedom.
APA:
Gold, T., Lomakin, A., Goller, T., Völz, A., & Graichen, K. (2020). Towards a Generic Manipulation Framework for Robots based on Model Predictive Interaction Control. In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 401 - 407). Beijing, CN.
MLA:
Gold, Tobias, et al. "Towards a Generic Manipulation Framework for Robots based on Model Predictive Interaction Control." Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA), Beijing 2020. 401 - 407.
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