A Human Arm’s Mechanical Impedance Tuning Method for Improving the Stability of Haptic Rendering

Abstract

SUMMARY Rendering of rigid objects with high stiffness while guaranteeing system stability remains a major and challenging issue in haptics. Being a part of the haptic system, the behavior of human operators, represented as the mechanical impedance of arm, has an inevitable influence on system performance. This paper first verified that the human arm impedance can unconsciously be modified through imposing background forces and resist unstable motions arising from external disturbance forces. Then, a reliable impedance tuning (IT) method for improving the stability and performance of haptic systems is proposed, which tunes human arm impedance by superimposing a position-based background force over the traditional haptic workspace. Moreover, an adaptive IT algorithm, adjusting the maximum background force based on the velocity of the human arm, is proposed to achieve a reasonable trade-off between system stability and transparency. Based on a three-degrees-of-freedom haptic device, maximum achievable stiffness and transparency grading experiments are carried out with 12 subjects, which verify the efficacy and advantage of the proposed method.

A Data Acquisition and Processing Method for Edge Computing Robotic Arm Behavior Recognition

“…The largest eigenvector obtained from this characteristic formula is the optimal PCA transform vector [12]. In the PCA dimensionality reduction process, it is usually necessary to manually adjust the reduced size [13]. The transformation matrix after dimensionality reduction can be…”

Robot Variable Impedance Skill Transfer and Learning Framework Based on a Simplified Human Arm Impedance Model

“…Substituting equation (12) into equation (11) and then taking equation (11) into equation 10, we obtain S R . To learn this model, we assume that the Gaussian noise affects the measurement of the stiffness matrix S iden (i).…”

“…Many researchers have performed static and dynamic analyses of the impedance parameters of the human arm [4]- [8]. The arm endpoint stiffness, as the most important impedance gain (among mass, damping, and stiffness) [9], greatly influences operation tasks [10], [11] in the form of an endpoint stiffness ellipsoid [12]. Many studies have revealed that the arm endpoint stiffness is mainly affected by arm configurations [13], [14] and the co-contraction effect of antagonistic muscles [15].…”