Impedance characteristic of human arm for cooperative robot (original) (raw)
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IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028), 1999
In the near future many aspect of life will be encompassed by tasks performed in co-operation with robots. As a result, robots need to be made human-friendly and to execute tasks in co-operation with humans. Control systems for such robots should be designed to work by imitating human characteristics. We aim to achieve these goals by controlling a simple one degree-of-freedom robot. First, the impedance characteristics of the human arm in a co-operative task are investigated. Then, these characteristics are implemented in a robot which performs a co-operative task with a human. The proposed control method produced good characteristics for robots co-operating with humans.
Impedance characteristic of the human arm during passive movements
IAES International Journal of Artificial Intelligence, 2023
This paper describes the impedance characteristics of the human arm during passive movement. The arm was moved in the desired trajectory. The motion was actuated by a 1-degree-of-freedom robot system. Trajectories used in the experiment were minimum jerk (the rate of change of acceleration) trajectories, which were found during a human and human cooperative task and optimum for muscle movement. As the muscle is mechanically analogous to a spring-damper system, a second-order equation was considered as the model for arm dynamics. In the model, inertia, stiffness, and damping factor were considered. The impedance parameters were estimated from the position and torque data obtained from the experiment and based on the "Estimation of Parametric Model". It was found that the inertia is almost constant over the operational time. The damping factor and stiffness were high at the starting position and became near zero after 0.4 seconds.
A model of force and impedance in human arm movements
Biological Cybernetics, 2004
This paper describes a simple computational model of joint torque and impedance in human arm movements that can be used to simulate three-dimensional movements of the (redundant) arm or leg and to design the control of robots and human-machine interfaces. This model, based on recent physiological findings, assumes that (1) the central nervous system learns the force and impedance to perform a task successfully in a given stable or unstable dynamic environment and (2) stiffness is linearly related to the magnitude of the joint torque and increased to compensate for environment instability. Comparison with existing data shows that this simple model is able to predict impedance geometry well.
Control of 3D Human Arm Impedance
2013
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, 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 the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
Impedance characteristics of a neuromusculoskeletal model of the human arm I. Posture control
Biological Cybernetics, 1999
The mechanical impedance of neuromusculoskeletal models of the human arm is studied in this paper. The model analysis provides a better understanding of the contributions of possible intrinsic and re¯exive components of arm impedance, makes clear the limitations of second-order mass-viscosity-stiness models and reveals possible task eects on the impedance. The musculoskeletal model describes planar movements of the upper arm and forearm, which are moved by six lumped muscles with nonlinear dynamics. The motor control system is represented by a neural network which combines feedforward and feedback control. It is optimized for the control of movements or for posture control in the presence of external forces. The achieved impedance characteristics depend on the conditions during the learning process. In particular, the impedance is adapted in a suitable way to the frequency content and direction of external forces acting on the hand during an isometric task. The impedance characteristics of a model, which is optimized for movement control, are similar to experimental data in the literature. The achieved stiness is, to a large extent, re¯exively determined whereas the approximated viscosity is primarily due to intrinsic attributes. It is argued that usually applied Hill-type muscle models do not properly represent intrinsic muscle stiness.
Characteristics of Human Arm Impedances: A Study on Daily Movement
2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, 2014
This paper presents the impedance characteristics of human arm in daily spatial activity. Human arm is considered as a mass-spring-damper system. The input data in the form of Cartesian position is measured to get dynamic impedance relationship by the motion equation for the mass-springdamper system. Mappings are done by various combinations to observe the nature of the different impedance components during dynamic movement. The significant amount of variation in damping and inertia components are observed in every turning of the arm movement while the stiffness shows the changing behavior throughout the movement. From this study it is known that for this particular movement the arm follows a pattern and same behavior is followed for the repetitions of the movement. The obtained result could be beneficial for the study of upper extremity exoskeleton for human rehabilitation.
2011 IEEE International Conference on Robotics and Biomimetics, 2011
This work introduces the concept of Tele-Impedance as a method for controlling/teleoperating a robotic arm in contact with the environment. Opposite to bilateral force-reflecting teleoperation control approach, which uses a position/velocity command combined with force feedback from the robot side, Tele-Impedance enriches the command sent to the slave robot by combining the position reference with a stiffness (or full impedance) reference. The desired stiffness profile is directly estimated from the arm of the human operating the remote robotic arm. We preliminarily investigate the effectiveness of this method while teleoperating a slave robotic arm to execute simple tasks. The KUKA light weight robotic arm is used as the slave manipulator. The endpoint (wrist) position of the human arm is monitored by an optical tracking system while the stiffness of the human arm is estimated from the electromyography (EMGs) signal measurements of four flexor-extensor muscle pairs, in realtime. The performance of Tele-Impedance control method is assessed by comparing the results obtained while executing a peg-in-hole task, with the slave arm under i) constant low stiffness, ii) constant high stiffness or iii) under Tele-Impedance control. The experimental results demonstrate the effectiveness of the Tele-Impedance control method and highlight its potential use to safely execute tasks with uncertain environment constraints which may result in large deviations from the commanded position trajectories.
An improved human-robot interface by measurement of muscle stiffness
2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 2012
Necessary physical contact between an operator and a force feedback haptic device creates a coupled system consisting of human and machine. This contact, combined with the natural human tendency to increase arm stiffness to attempt to stabilize its motion, can reduce the stability of the system. This paper proposes a method to increase stability on demand while maintaining speed and performance. Operator arm stiffness is not directly measurable, so controllers cannot typically account for this issue. The causes of arm end-point stiffness are examined as related to system stability, and a method for estimating changes in arm stiffness based on arm muscle activity was designed to provide a robotic controller with additional information about the operator. This was accomplished using EMGs to measure muscle activities and estimating the level of arm stiffness, which was used to adjust the dynamic characteristics of an impedance controller. To support this design, the correlation between EMGs and arm stiffness was validated experimentally. Further experiments characterized the effects of the designed system on operator performance. This showed increased stability and faster, more accurate movements using the compensating system. Such a system could be used in many applications, including force assisting devices in industrial facilities.
Mapping of human arm impedance characteristics in spatial movements
Bulletin of Electrical Engineering and Informatics, 2022
In this paper, impedance characteristics are determined for discrete movement. It explores the changes in impedance characteristics of human arm during a complete task. This study considered 3D spatial movement for horizontal adduction and abduction. The human arm is considered as mass-spring-damper system and the modelling is done accordingly. The model is solved for 3 degree of freedom (3DoF) spatial movement usually used for daily work. Inertia, stiffness and damping factor are the impedance characteristics considered in the model. Using position measuring device, the position data of elbow and wrist were obtained with respect to pre-defined references. The data were used to calculate velocity, acceleration and force. Then, the impedance characteristics were determined by solving the equation of motion of the mass-spring-damper system corresponding to different position of the wrist on the trajectory. These impedance factors were then plotted to map the characteristics. The mappi...
Conditioning vs. excitation time for estimating impedance parameters of the human arm
2011 11th IEEE-RAS International Conference on Humanoid Robots, 2011
The human arm's capability to alter its impedance has motivated multiple developments of robotic manipulators and control methods. It provides advantages during manipulation such as robustness against external disturbances and task adaptability. However, how the impedance of the arm is set depends on the manipulation situation; a general procedure is lacking. This paper aims to fill this gap by providing a method to estimate the impedance parameters of the human arm, while taking the numerical stability of the approach into account. A dynamic arm model and an identification method is presented. Confidential criteria to determine the accuracy of the estimated parameters are given. Finally, the procedure is validated in an experiment with a human subject and the results are discussed.