Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Autor: Pau Muñoz-Benavent, Jaime Valls Miro, Luis Gracia, Alicia Esparza, Josep Tornero, J. Ernesto Solanes
Rok vydání: 2018
Předmět:
Zdroj: RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
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ISSN: 0736-5845
Popis: [EN] This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown.
This work was supported in part by the Spanish Government under the Project DPI2017-87656-C2-1-R and the Generalitat Valenciana under Grants VALi+d APOSTD/2016/044 and BEST/2017/029.
Databáze: OpenAIRE
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