Hassas Kavrama Görevinde Robot Elin Kavrama Kuvvetinin Bulanık Kontrolü için Güvenlik Marjı Veri Tabanının Elde Edilmesi

Year 2021, Issue: 24, 321 - 327, 15.04.2021

Canfer İşlek , Ersin Özdemir

https://doi.org/10.31590/ejosat.900166

Abstract

Bu çalışmanın amacı, bir robot elin kavrama kuvvetinin kontrolünün bulanık mantık denetleyici ile yapılabilmesi için gerekli parametrelerin ayarlanması amacıyla insanların hassas kavrama yeteneğine ait verilerin toplanmasıdır. Literatürde, insanların nesneleri kavrayıp kaldırırken minimum kavrama kuvvetinin üzerine ekledikleri fazladan kuvvet, güvenlik marjı olarak ifade edilmektedir. Bu çalışmada insanlarla farklı ağırlıkta ve farklı yüzey özelliklerinde nesneler için hassas kavrama ve kaldırma deneyleri yapılmıştır. Yapılan deneylerde, insanların hassas kavrama görevinde farklı ağırlıkta ve yüzey özelliklerindeki nesneleri kavrayıp kaldırırken uyguladıkları güvenlik marjı verileri elde edilmiştir. Elde edilen güvenlik marjı verileri, tasarlanacak olan bulanık mantık denetleyicinin veri tabanı olarak değerlendirilecektir. Böylelikle bir robot elin, özellikleri bilinmeyen bir nesneyi hassas bir şekilde kavrayıp kaldırabilmesi sağlanacaktır. Yapılan deneyler sonucunda değişen nesne ağırlığına ve yüzey sürtünme katsayısına bağlı olarak %9 ile %20 arasında değişen güvenlik marjı oranları elde edilmiştir. Bu çalışma ile robot elin kavrama kuvveti kontrolü için bulanık mantık tabanlı, değişken güvenlik marjı odaklı bir kavrama kuvveti kontrol yaklaşımı ortaya konulmuştur.

Keywords

Güvenlik marjı, Robot el, Kavrama kuvveti, Hassas kavrama

Supporting Institution

Mustafa Kemal Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü

Project Number

9861

Thanks

Bu çalışmayı 9861 proje numarası ile destekleyen Mustafa Kemal Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğüne teşekkür ederiz.

Obtaining the Safety Margin Database for Fuzzy Control of the Grip Force of Robotic Hand in the Precision Grasp Task

Abstract

The aim of this study is to collect data on human’s precise grip ability in order to adjust the parameters required to control the grip force of a robotic hand with a fuzzy logic controller. In the literature, the extra force that humans add on over of the minimum grip force when grasping and lifting objects is expressed as the safety margin. In this study, precision grip and lifting experiments were carried out for objects of different weights and different surface properties. In the experiments, the safety margin data that people apply while grasping and lifting objects of different weights and different surface properties in precision grasping were obtained. The obtained safety margin data will be evaluated as the database of the fuzzy logic controller to be designed. In this way, it will be ensured that a robotic hand can grip and lift an unknown object precisely. As a result of the experiments, safety margin rates varying between 9% and 20% were obtained depending on the varying object weight and coefficient of friction of surface. In this study, a fuzzy logic-based, variable safety margin-oriented grip force control approach is presented for robotic hand grip force control.

Keywords

Safety margin, Robotic hand, Grasping force, Precision grasp

Project Number

9861

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