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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zimmerman, T.G., Smith, J.R., Paradiso, J.A., Allport, D., Gershenfeld, N.: Applying electric field sensing to human-computer interfaces. In: Proceedings of ACM Conference on Human Factors in Computing Systems (CHI 1995), Denver, CO, pp. 280–287 (1995)
Nehmzow, U.: Mobile Robotics: A Practical Introduction. Springer, London (2000)
Bicchi, A.: Hands for dexterous manipulation and powerful grasping: A difficult road towards simplicity. IEEE Transactions on Automatic Control 45(9), 652–662 (2000)
Dubey, V.N.: Sensing and Control Within a Robotic End Effector. PhD thesis, University of Southampton, Southampton, UK (1997)
Goguen, J.A.: On fuzzy robot planning. In: Zadeh, L.A., Fu, K.-S., Tanaka, K., Shimura, M. (eds.) Fuzzy Sets and their Applications to Cognitive and Decision Processes, pp. 429–448. Academic Press, New York (1975)
de Silva, C.W.: Applications of fuzzy logic in the control of robotic manipulators. Fuzzy Sets and Systems 70(2-3), 223–234 (1995)
Kim, D., Rhee, S.: Design of a robust fuzzy controller for the arc stability of CO 2 welding process using Taguchi method. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 32(2), 157–162 (2002)
Mamdani, E.H.: Twenty years of fuzzy control: experiences gained and lessons learnt. In: Proceedings of IEEE International Conference on Fuzzy Systems, San Francisco, CA, vol. 1, pp. 339–344 (1993)
Jantzen, J.: Design of fuzzy controllers. Technical Report 98-E-864 (design), Technical University of Denmark, Department of Automation, Lyngby, Denmark (1998)
Driankov, D., Hellendoorn, H., Reinfrank, M.: An Introduction to Fuzzy Control. Springer, New York (1993)
Dubey, V.N., Crowder, R.M., Chappell, P.H.: Optimal object grasp using tactile sensors and fuzzy logic. Robotica 17, 685–693 (1999)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (2000)
Harris, C.J., Hong, X., Gan, Q.: Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/11579427_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
Online ISBN: 978-3-540-31653-4
eBook Packages: Computer ScienceComputer Science (R0)