2014 IEEE/RSJ International Conference on Intelligent Robots and Systems 2014
DOI: 10.1109/iros.2014.6943237
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Implicit force control for an industrial robot with flexible joints and flexible links

Abstract: The main purpose of this paper is to present an implicit force control scheme for 6 DoF industrial robots, whose compliance model takes into account both joint and link elasticities. The system composed by the robot and the environment is modeled by means of a simple equivalent elasticity at the end effector. A method to avoid limit cycles due to friction during force control applications is then proposed. The compliance model and the force control are experimentally validated on a industrial robot equipped wi… Show more

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Cited by 9 publications
(4 citation statements)
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References 11 publications
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“…Applications of implicit force control have been presented in Kröger et al (2004), Osypiuk et al (2006), and Winkler and Suchy (2016). Rossi et al (2014Rossi et al ( , 2016 discussed the effects of joint and link elasticities in the performance of implicit force control, while Parigi Polverini et al (2017) applied advanced methods based on set invariance to design an implicit force controller.…”
Section: Overviewmentioning
confidence: 99%
“…Applications of implicit force control have been presented in Kröger et al (2004), Osypiuk et al (2006), and Winkler and Suchy (2016). Rossi et al (2014Rossi et al ( , 2016 discussed the effects of joint and link elasticities in the performance of implicit force control, while Parigi Polverini et al (2017) applied advanced methods based on set invariance to design an implicit force controller.…”
Section: Overviewmentioning
confidence: 99%
“…Given the human arm stiffness model described in Section 3, the manipulator stiffness matrices as reported in [40], and applying the procedure introduced in Section 4, the minimum damping that stabilises the system for three different values of the virtual tool mass -2 Kg, 25 Kg, 50 Kg -, and for the five human arm postures considered in the identification process can be determined.…”
Section: Admittance Filter Tuningmentioning
confidence: 99%
“…The equivalent mass M rj in the j-th Cartesian direction (j = x, y, z), depending on the robot configuration q, is given by [39] M rj = 1 e T j [J(q)B −1 (q)J T (q)] e j where J(q) and B(q) are the geometric Jacobian and the generalized mass matrix of the robot, respectively, q is the joint position vector, and e j is a unitary vector defined as follows Similarly, the equivalent stiffness K rj in the j-th Cartesian direction (j = x, y, z), depending on the robot configuration q, is given by [40] K rj = 1 e T j C ee e j where the end-effector compliance C ee is composed by two different contributions, one related to lumped joint compliance and the other one due to distributed arm stiffness, i.e.,…”
mentioning
confidence: 99%
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