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.

在这项研究中，目的是使用机械手抓取和提起未知物体，而不会对其形状造成任何永久性变化。当人们举起物体时，他们会在抓握力的最小极限值以上添加额外的力量以确保安全。这种额外的力在文献中表示为“安全裕度”。在进行的研究中，安全裕度被最小化并控制了抓握力。为此，开发的系统测量了人类抓取物体的安全裕度性能。对获得的数据进行模糊逻辑控制器（FLC）评估，并设计了模糊安全裕度推导系统（SMDS）。在文献中，据报道安全边际率在 10% 到 40% 之间变化。作为本研究的基础，在测量人类抓地力性能的实验研究中，对于不同的表面摩擦特性和不同的重量，获得了 9% 到 20% 的安全裕度比率。作为在本研究中介绍的 FLC 的 Matlab/Simulink 环境中进行的性能测试的结果，对于不同的表面摩擦特性和重量，获得了 8% 到 21% 的安全裕度比率。据观察，所开发系统的性能测试结果与人类性能数据非常接近。所得结果表明，所设计的模糊SMDS可以安全地用于抓握力的控制，以实现机器人手的精确抓握任务。作为这项研究中在FLAT的Matlab / Simulink环境中进行的性能测试的结果，对于不同的表面摩擦性能和重量，获得了8％至21％的安全裕度比。据观察，所开发系统的性能测试结果与人类性能数据非常接近。获得的结果表明，设计的模糊 SMDS 可以安全地用于控制机械手精确抓取任务的抓取力。作为在本研究中介绍的 FLC 的 Matlab/Simulink 环境中进行的性能测试的结果，对于不同的表面摩擦特性和重量，获得了 8% 到 21% 的安全裕度比率。据观察，所开发系统的性能测试结果与人类性能数据非常接近。所得结果表明，所设计的模糊SMDS可以安全地用于抓握力的控制，以实现机器人手的精确抓握任务。