Modeling the Coupled Difference Threshold of Perceiving Mass and Stiffness from Force

Just notable difference (JND) thresholds for the perception of manipulator dynamic properties are relevant for tele-operation and simulation of vehicles. Manipulator dynamic properties are characterized by multiple variables (describing mass, spring and damping for a linear manipulator) and the JND threshold for any of these variables is affected by variation in the remaining variables. In previous work, we demonstrated and modeled the coupling of the stiffness JND and the mass JND, and investigated the effects of stiffness and mass properties on the damping JND. In this work we investigate how changes in the damping parameter affect the JND in perceiving stiffness and mass. In an experiment our subjects were instructed to discriminate between different levels of manipulator's stiffness or mass, while tracking a prescribed sinusoidal manipulator movement. Results show that the JND in spring force and the JND in inertia force are identical, and increase for higher damping levels. The JND model developed in our previous work can successfully describe the experimental observations, thereby providing an extension of Weber's law. The impedance of the manipulator is considered as the reference stimulus in the frequency domain, so that a single ratio describes the JND thresholds for all three properties.

[1]  Blake Hannaford,et al.  Control law design for haptic interfaces to virtual reality , 2002, IEEE Trans. Control. Syst. Technol..

[2]  Max Mulder,et al.  The Influence of Discrimination Strategy on the JND in Human Haptic Perception of Manipulator Stiffness , 2017 .

[3]  N. Durlach,et al.  Manual discrimination of force using active finger motion , 1991, Perception & psychophysics.

[4]  Claudio Melchiorri,et al.  Control schemes for teleoperation with time delay: A comparative study , 2002, Robotics Auton. Syst..

[5]  René van Paassen,et al.  An Empirical Human Controller Model for Preview Tracking Tasks , 2016, IEEE Transactions on Cybernetics.

[6]  René van Paassen,et al.  On the relationship between the force JND and the stiffness JND in haptic perception , 2017, SAP.

[7]  Daniel M. Wolpert,et al.  Forward Models for Physiological Motor Control , 1996, Neural Networks.

[8]  J. A. Mulder,et al.  Model of the Neuromuscular Dynamics of the Human Pilot's Arm , 2004 .

[9]  Blake Hannaford,et al.  Stability and performance tradeoffs in bi-lateral telemanipulation , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[10]  Dale A. Lawrence Stability and transparency in bilateral teleoperation , 1993, IEEE Trans. Robotics Autom..

[11]  M A Srinivasan,et al.  Manual discrimination of compliance using active pinch grasp: The roles of force and work cues , 1995, Perception & psychophysics.

[12]  Max Mulder,et al.  Modeling Human Difference Threshold in Perceiving Mechanical Properties From Force , 2018, IEEE Transactions on Human-Machine Systems.

[13]  Sandra Hirche,et al.  Masking Effects for Damping JND , 2012, EuroHaptics.

[14]  Yoshiyuki Tanaka,et al.  Motion Dependence of Impedance Perception Ability in Human Movements , 2005 .

[15]  L. Jones Kinesthetic Sensing , 2000 .

[16]  David A. Abbink,et al.  Framework for Human Haptic Perception With Delayed Force Feedback , 2019, IEEE Transactions on Human-Machine Systems.

[17]  Mandayam A. Srinivasan,et al.  Manual resolution of viscosity and mass , 1995 .

[18]  Max Mulder,et al.  Objective Inceptor Cueing Test for Control Loading Systems : Principle and Initial Design , 2017 .

[19]  N. Prins Psychophysics: A Practical Introduction , 2009 .