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In-hand recognition and manipulation of elastic objects using a servo-tactile control strategy

Authors :
A. Delgado
Carlos A. Jara
Fernando Torres
Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal
Universidad de Alicante. Instituto Universitario de Investigación Informática
Automática, Robótica y Visión Artificial
Source :
RUA. Repositorio Institucional de la Universidad de Alicante, Universidad de Alicante (UA)
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Grasping and manipulating objects with robotic hands depend largely on the features of the object to be used. Especially, features such as softness and deformability are crucial to take into account during the manipulation tasks. Indeed, positions of the fingers and forces to be applied by the robot hand when manipulating an object must be adapted to the caused deformation. For unknown objects, a previous recognition stage is usually needed to get the features of the object, and the manipulation strategies must be adapted depending on that recognition stage. To obtain a precise control in the manipulation task, a complex object model is usually needed and performed, for example using the Finite Element Method. However, these models require a complete discretization of the object and they are time-consuming for the performance of the manipulation tasks. For that reason, in this paper a new control strategy, based on a minimal spring model of the objects, is presented and used for the control of the robot hand. This paper also presents an adaptable tactile-servo control scheme that can be used in in-hand manipulation tasks of deformable objects. Tactile control is based on achieving and maintaining a force value at the contact points which changes according to the object softness, a feature estimated in an initial recognition stage. Research supported by Spanish Ministry of Economy, European FEDER funds, the Valencia Regional Government and University of Alicante, through projects DPI2012-32390, DPI2015-68087-R, PROMETEO/2013/085 and GRE 15-05.

Details

ISSN :
07365845
Volume :
48
Database :
OpenAIRE
Journal :
Robotics and Computer-Integrated Manufacturing
Accession number :
edsair.doi.dedup.....7f89e6f7e7c1fc515374715e4298f6a9