Design of a fuzzy safety margin derivation system for grip force control of robotic hand in precision grasp task
Open Access
- 1 May 2021
- journal article
- research article
- Published by SAGE Publications in International Journal of Advanced Robotic Systems
- Vol. 18 (3)
Abstract
In this study, the aim was to grasp and lift an unknown object without causing any permanent change on its shape using a robotic hand. When people lift objects, they add extra force for safety above the minimum limit value of the grasp force. This extra force is expressed as the “safety margin” in the literature. In the conducted study, the safety margin is minimized and the grasp force was controlled. For this purpose, the safety margin performance of human beings for object grasping was measured by the developed system. The obtained data were assessed for a fuzzy logic controller (FLC), and the fuzzy safety margin derivation system (SMDS) was designed. In the literature, the safety margin rate was reported to vary between 10% and 40%. To be the basis for this study, in the experimental study conducted to measure the grip performance of humans, safety margin ratios ranging from 9% to 20% for different surface friction properties and different weights were obtained. As a result of performance tests performed in Matlab/Simulink environment of FLC presented in this study, safety margin ratios ranging from 8% to 21% for different surface friction properties and weights were obtained. It was observed that the results of the performance tests of the developed system were very close to the data of human performance. The results obtained demonstrate that the designed fuzzy SMDS can be used safely in the control of the grasp force for the precise grasping task of a robot hand.Keywords
Funding Information
- the Mustafa Kemal University Scientific Research Projects Coordinatorship (9861)
This publication has 20 references indexed in Scilit:
- More Than a Feeling: Learning to Grasp and Regrasp Using Vision and TouchIEEE Robotics and Automation Letters, 2018
- Grasping Force Control for a Robotic Hand by Slip Detection Using Developed Micro Laser Doppler VelocimeterSensors, 2018
- Analysis of coordinated grasping kinematics and optimization of grasping force of a parallel hybrid handInternational Journal of Advanced Robotic Systems, 2017
- Robust contact force controller for slip prevention in a robotic gripperProceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2010
- Friction Estimation by Pressing an Elastic Finger-Shaped Sensor Against a SurfaceIEEE Transactions on Robotics and Automation, 2004
- Fuzzy logic grasp control using tactile sensorsMechatronics, 2001
- Optimal object grasp using tactile sensors and fuzzy logicRobotica, 1999
- Human Grasp Choice and Robotic Grasp Analysis1990
- On grasp choice, grasp models, and the design of hands for manufacturing tasksIEEE Transactions on Robotics and Automation, 1989
- Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objectsExperimental Brain Research, 1984