Abstract
Robotic end effectors are used over a diverse range of applications where they are required to grip with optimal force to avoid the object be either dropped or crushed. The slipping state can be easily detected by the output of the slip sensor. When the output has a non-zero value, the object is slipping. Conversely, detecting the deformation (crushing) state is more difficult, especially in an unstructured environment. Current proposed methodologies are ad hoc and specialised to the particular object or objects to be handled. Consequently, the gripper can only manipulate prior known objects, constraining the gripper application to a small set of predetermined objects. Accordingly, in this paper, it is proposed a hybrid approach of fuzzy and expert systems that permits to detect when an unknown object is being deformed. To determinate when the gripped object is being deformed, the fuzzy/expert system uses information from three sensors: applied force, slip rate and finger position. Several objects of different characteristics were used to prove the effectiveness of the proposed approach.
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Domínguez-López, J.A., Marrufo, G. (2005). Hybrid Fuzzy/Expert System to Control Grasping with Deformation Detection. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_104
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DOI: https://doi.org/10.1007/11579427_104
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