Influence of mechanical impedance of human arm on the stability of haptic rendering

2012 ◽  
Author(s):  
Hao Zhao ◽  
Chen-xi Xu ◽  
Xiong Lu
Keyword(s):  
Mechanical Impedance ◽  
Haptic Rendering ◽  
Human Arm ◽  
The Stability

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

Robotica ◽  
2020 ◽  
pp. 1-13
Author(s):  
Xiong Lu ◽  
Beibei Qi ◽  
Hao Zhao ◽  
Junbin Sun
Keyword(s):  
Degrees Of Freedom ◽  
External Disturbance ◽  
Mechanical Impedance ◽  
System Stability ◽  
Tuning Method ◽  
Rigid Objects ◽  
Human Arm ◽  
Human Operators ◽  
And Performance ◽  
The Stability

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.

Regulation of 3D Human Arm Impedance Through Muscle Co-Contraction

2013 ◽  
Author(s):  
Harshil Patel ◽  
Gerald O’Neill ◽  
Panagiotis Artemiadis
Keyword(s):  
Dimensional Space ◽  
Human Subjects ◽  
Three Dimensional ◽  
Mechanical Impedance ◽  
Dominant Factor ◽  
Robot Arm ◽  
End Point ◽  
Human Arm ◽  
Arm Muscles ◽  
Experimental Trials

Humans have the inherent ability of performing highly dexterous and skillful tasks with their arms, involving maintenance of posture, movement, and interaction with the environment. The latter requires the human to control the dynamic characteristics of the upper limb musculoskeletal system. These characteristics are quantitatively represented by inertia, damping, and stiffness, which are measures of mechanical impedance. Many previous studies have shown that arm posture is a dominant factor in determining the end point impedance on a horizontal (transverse) plane. This paper presents the characterization of the end point impedance of the human arm in three-dimensional space. Moreover, it models the regulation of the arm impedance with respect to various levels of muscle co-contraction. The characterization is made by route of experimental trials where human subjects maintained arm posture while their arms were perturbed by a robot arm. Furthermore, the subjects were asked to control the level of their arm muscles’ co-contraction, using visual feedback of their muscles’ activation, in order to investigate the effect of this muscle co-contraction on the arm impedance. The results of this study show a very interesting, anisotropic increase of arm stiffness due to muscle co-contraction. These results could lead to very useful conclusions about the human’s arm biomechanics, as well as many implications for human motor control-specifically the control of arm impedance through muscle co-contraction.

scholarly journals A variable admittance control strategy for stable physical human–robot interaction

2019 ◽  
Vol 38 (6) ◽  
pp. 747-765 ◽  
Author(s):  
Federica Ferraguti ◽  
Chiara Talignani Landi ◽  
Lorenzo Sabattini ◽  
Marcello Bonfè ◽  
Cesare Fantuzzi ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Admittance Control ◽  
Robot Interaction ◽  
Interaction Control ◽  
Human Arm ◽  
Industrial Operations ◽  
Novel Method ◽  
The Stability ◽  
Stability Issues ◽  
Human Robot Collaboration

Admittance control allows a desired dynamic behavior to be reproduced on a non-backdrivable manipulator and it has been widely used for interaction control and, in particular, for human–robot collaboration. Nevertheless, stability problems arise when the environment (e.g. the human) the robot is interacting with becomes too stiff. In this paper, we investigate the stability issues related to a change of stiffness of the human arm during the interaction with an admittance-controlled robot. We propose a novel method for detecting the rise of instability and a passivity-preserving strategy for restoring a stable behavior. The results of the paper are validated on two robotic setups and with 50 users performing two tasks that emulate industrial operations.

Analysis of mechanical impedance in human arm movements using a virtual tennis system

2004 ◽  
Vol 91 (5) ◽  
pp. 295-305 ◽  
Author(s):  
Toshio Tsuji ◽  
Yusaku Takeda ◽  
Yoshiyuki Tanaka
Keyword(s):  
Arm Movements ◽  
Mechanical Impedance ◽  
Human Arm ◽  
Human Arm Movements

scholarly journals An Adaptive Assistance Controller to Optimize the Exoskeleton Contribution in Rehabilitation

Robotics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 95
Author(s):  
Rezvan Nasiri ◽  
Mohammad Shushtari ◽  
Arash Arami
Keyword(s):  
Tracking Error ◽  
Adaptive Method ◽  
Convergence Time ◽  
Task Completion ◽  
Pd Controller ◽  
Convergence Proof ◽  
Human Arm ◽  
Simulation Results ◽  
The Stability ◽  
Adaptive Feedforward

In this paper, we present a novel adaptation rule to optimize the exoskeleton assistance in rehabilitation tasks. The proposed method adapts the exoskeleton contribution to user impairment severity without any prior knowledge about the user motor capacity. The proposed controller is a combination of an adaptive feedforward controller and a low gain adaptive PD controller. The PD controller guarantees the stability of the human-exoskeleton system during feedforward torque adaptation by utilizing only the human-exoskeleton joint positions as the sensory feedback for assistive torque optimization. In addition to providing a convergence proof, in order to study the performance of our method we applied it to a simplified 2-DOF model of human-arm and a generic 9-DOF model of lower limb to perform walking. In each simulated task, we implemented the impaired human torque to be insufficient for the task completion. Moreover, the scenarios that violate our convergence proof assumptions are considered. The simulation results show a converging behavior for the proposed controller; the maximum convergence time of 20 s is observed. In addition, a stable control performance that optimally supplements the remaining user motor contribution is observed; the joint angle tracking error in steady condition and its improvement compared to the start of adaptation are as follows: shoulder 0.96±2.53° (76%); elbow −0.35±0.81° (33%); hip 0.10±0.86° (38%); knee −0.19±0.67° (25%); and ankle −0.05±0.20° (60%). The presented simulation results verify the robustness of proposed adaptive method in cases that differ from our mathematical assumptions and indicate its potentials to be used in practice.

scholarly journals Haptic force rendering of rigid-body interactions: A systematic review

2021 ◽  
Vol 13 (9) ◽  
pp. 168781402110415
Author(s):  
Yang Wang ◽  
Lei Feng ◽  
Kjell Andersson
Keyword(s):  
Systematic Review ◽  
Rigid Body ◽  
Haptic Rendering ◽  
Body Interaction ◽  
The Stability ◽  
Technical Terms

Haptic rendering has been developing for decades with different rendering approaches and many factors that affect the stability when rendering rigid-body interactions have been investigated. To get an overall understanding of the challenges in haptic rendering, we approach this topic by conducting a systematic review. This review examines different haptic rendering approaches and how to deal with instability factors in rendering. A total of 25 papers are reviewed to answer the following questions: (1) what are the most common haptic rendering approaches for rigid-body interaction? and (2) what are the most important factors for instability of haptic rendering and how to address them? Through the process of investigating these questions, we get the insight that transparency can be further explored and technical terms to describe haptic rendering can be more standardized to push the topic forward.

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