Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface

Human Stabilization of Delay-Induced Instability of Haptic Rendering in a Stiffness Discrimination Task

Towards developing a coupled stability theory for haptic systems, we study the interaction of operators with time-delayed force feedback. In this work, we analyzed and validated experimentally the stability boundaries of an uncoupled system - without considering the human. We then designed an experiment in which the participants used a haptic device to interact with virtual elastic force fields in a stiffness discrimination task. We compared the performance and kinematics of users in uncoupled-unstable and uncoupled-stable conditions and characterized the stabilizing contribution of the users. We found that the users were able to perform the task regardless of the uncoupled-stability conditions. In addition, in uncoupled-unstable conditions, users maintained movement characteristics that were important for exploratory mediation, such as depth and duration of the movement, whereas other characteristics were not preserved. The results were reproduced in a simulation of the human controller that combined an inverse model and an optimal feedback controller. Adequate performance under the uncoupled-unstable yet coupled-stable conditions supports the potential benefit of designing for coupled stability of haptic systems. This could lead to the use of less conservative controllers than state-of-the-art solutions in haptic and teleoperation systems, and advance the fidelity of haptic feedback.

HRpI System Based on Wavenet Controller with Human Cooperative-in-the-Loop for Neurorehabilitation Purposes

There exist several methods aimed at human-robot physical interaction (HRpI) to provide physical therapy in patients. The use of haptics has become an option to display forces along a given path so as to it guides the physiotherapist protocol. Critical in this regard is the motion control for haptic guidance to convey the specifications of the clinical protocol. Given the inherent patient variability, a conclusive demand of these HRpI methods is the need to modify online its response with neither rejecting nor neglecting interaction forces but to process them as patient interaction. In this paper, considering the nonlinear dynamics of the robot interacting bilaterally with a patient, we propose a novel adaptive control to guarantee stable haptic guidance by processing the causality of patient interaction forces, despite unknown robot dynamics and uncertainties. The controller implements radial basis neural network with daughter RASP1 wavelets activation function to identify the coupled interaction dynamics. For an efficient online implementation, an output infinite impulse response filter prunes negligible signals and nodes to deal with overparametrization. This contributes to adapt online the feedback gains of a globally stable discrete PID regulator to yield stiffness control, so the user is guided within a perceptual force field. Effectiveness of the proposed method is verified in real-time bimanual human-in-the-loop experiments.

Characterizing Detection Thresholds for Six Orthogonal Modes of Vibrotactile Display Via Stylus With Precision Grasp

In this paper, we characterize the detection thresholds in six orthogonal modes of vibrotactile haptic display via stylus, including three orthogonal force directions and three orthogonal torque directions at the haptic interaction point. A psychophysical study is performed to determine detection thresholds over the frequency range 20-250 Hz, for six distinct styluses. Analysis of variance is used to test the hypothesis that force signals, as well as torque signals, applied in different directions have different detection thresholds. We find that people are less sensitive to force signals parallel to the stylus than to those orthogonal to the stylus at low frequencies, and far more sensitive to torque signals about the stylus than to those orthogonal to the stylus. Optimization techniques are used to determine four independent two-parameter models to describe the frequency-dependent thresholds for each of the orthogonal force and torque modes for a stylus that is approximately radially symmetric; six independent models are required if the stylus is not well approximated as radially symmetric. Finally, we provide a means to estimate the model parameters given stylus parameters, for a range of styluses, and to estimate the coupling between orthogonal modes.

Impedance-Based Gaussian Processes for Modeling Human Motor Behavior in Physical and Non-Physical Interaction

OBJECTIVE

Modeling of human motor intention plays an essential role in predictively controlling a robotic system in human-robot interaction tasks. In most machine learning techniques, human motor behavior is modeled as a generic stochastic process. However, the integration of a priori knowledge about underlying system structures can provide insights on otherwise unobservable intrinsic states that yield the superior prediction performance and increased generalization capabilities.

METHODS

We present a novel method for modeling human motor behavior that explicitly includes a neuroscientifically supported model of human motor control, in which the dynamics of the human arm are modeled by a mechanical impedance that tracks a latent desired trajectory. We adopt a Bayesian setting by defining Gaussian process (GP) priors for the impedance elements and the latent desired trajectory. This enables exploitation of a priori human arm impedance knowledge for regression of interaction forces through inference of a latent desired human trajectory.

RESULTS

The method is validated using simulated data, with particular focus on effects of GP prior parameterization and intention estimation capabilities. The superior prediction performance is shown with respect to a naive GP prior. An experiment with human participants evaluates generalization capabilities and effects of training data sparsity.

CONCLUSION

We derive the correlations of an impedance-based GP model of human motor behavior that exploits a priori knowledge.

SIGNIFICANCE

The model effectively predicts interaction forces by inferring a latent desired human trajectory in previously observed as well as unobserved regions of the input space.

Motion planning strategies in human control of non-rigid objects with internal degrees of freedom

The paper deals with modeling of human-like reaching movements in dynamic environments. A simple but not trivial example of reaching in a dynamic environment is the rest-to-rest manipulation of a multi-mass flexible object with the elimination of residual vibrations. Two approaches to the prediction of reaching movements are formulated in position and force actuation settings. In the first approach, either the position of the hand or the hand force is specified by the lowest order polynomial satisfying the boundary conditions of the reaching task. The second approach is based on the minimization of either the hand jerk or the hand force-change, with taking into account the dynamics of the flexible object. To verify the resulting four mathematical models, an experiment on the manipulation of a ten-masses flexible object of low stiffness is conducted. The experimental results show that the second approach gives a significantly better prediction of human movements, with the minimum hand force-change model having a slight but consistent edge over the minimum hand jerk one.

Operator dynamics for stability condition in haptic and teleoperation system: A survey

BACKGROUND

Currently, haptic systems ignore the varying impedance of the human hand with its countless configurations and thus cannot recreate the complex haptic interactions. The literature does not reveal a comprehensive survey on the methods proposed and this study is an attempt to bridge this gap.

METHODS

The paper includes an extensive review of human arm impedance modeling and control deployed to address inherent stability and transparency issues in haptic interaction and teleoperation systems.

RESULTS

Detailed classification and comparative study of various contributions in human arm modeling are presented and summarized in tables and diagrams.

CONCLUSION

The main challenges in modeling human arm impedance for haptic robotic applications are identified. The possible future research directions are outlined based on the gaps identified in the survey.

Position calibration of a 3-DOF hand-controller with hybrid structure

A hand-controller is a human-robot interactive device, which measures the 3-DOF (Degree of Freedom) position of the human hand and sends it as a command to control robot movement. The device also receives 3-DOF force feedback from the robot and applies it to the human hand. Thus, the precision of 3-DOF position measurements is a key performance factor for hand-controllers. However, when using a hybrid type 3-DOF hand controller, various errors occur and are considered originating from machining and assembly variations within the device. This paper presents a calibration method to improve the position tracking accuracy of hybrid type hand-controllers by determining the actual size of the hand-controller parts. By re-measuring and re-calibrating this kind of hand-controller, the actual size of the key parts that cause errors is determined. Modifying the formula parameters with the actual sizes, which are obtained in the calibrating process, improves the end position tracking accuracy of the device.

On Configuration Trajectory Formation in Spatiotemporal Profile for Reproducing Human Hand Reaching Movement

Most functional reaching activities in daily living generally require a hand to reach the functional position in appropriate orientation with invariant spatiotemporal profile. Effectively reproducing such spatiotemporal feature of hand configuration trajectory in real time is essential to understand the human motor control and plan human-like motion on anthropomorphic robotic arm. However, there are no novel computational models in literature toward reproducing hand configuration-to-configuration movement in spatiotemporal profile. In response to the problem, this paper presents a computational framework for hand configuration trajectory formation based on hierarchical principle of human motor control. The composite potential field is constructed on special Euclidean Group to induce time-varying configuration toward target. The dynamic behavior of hand is described by a second-order kinematic model to produce the external representation of high-level motor control. The multivariate regression relation between intrinsic and extrinsic coordinates of arm, is statistically analyzed for determining the arm orientation in real time, which produces the external representation of low-level motor control. The proposed method is demonstrated in an anthropomorphic arm by performing several highly curved self-reaching movements. The generated configuration trajectories are compared with actual human movement in spatiotemporal profile to validate the proposed method.

End-point impedance measurements across dominant and nondominant hands and robotic assistance with directional damping

The goal of this paper is to perform end-point impedance measurements across dominant and nondominant hands while doing airbrush painting and to use the results for developing a robotic assistance scheme. We study airbrush painting because it resembles in many ways manual welding, a standard industrial task. The experiments are performed with the 7 degrees of freedom KUKA lightweight robot arm. The robot is controlled in admittance using a force sensor attached at the end-point, so as to act as a free-mass and be passively guided by the human. For impedance measurements, a set of nine subjects perform 12 repetitions of airbrush painting, drawing a straight-line on a cartoon horizontally placed on a table, while passively moving the airbrush mounted on the robot's end-point. We measure hand impedance during the painting task by generating sudden and brief external forces with the robot. The results show that on average the dominant hand displays larger impedance than the nondominant in the directions perpendicular to the painting line. We find the most significant difference in the damping values in these directions. Based on this observation, we develop a "directional damping" scheme for robotic assistance and conduct a pilot study with 12 subjects to contrast airbrush painting with and without robotic assistance. Results show significant improvement in precision with both dominant and nondominant hands when using robotic assistance.

Research of a New 6-Dof Force Feedback Hand Controller System

The field of teleoperation with force telepresence has expanded its scope to include manipulation at different scales and in virtual worlds, and the key component of which is force feedback hand controller. This paper presents a novel force feedback hand controller system, including a 3-dof translational and 3-dof rotational hand controllers, respectively, to implement position and posture teleoperation of the robot end effector. The 3-dof translational hand controller adopts innovative three-axes decoupling structure based on the linear motor; the 3-dof rotational hand controller adopts serial mechanism based on three-axes intersecting at one point, improving its overall stiffness. Based on the kinematics, statics, and dynamics analyses for two platforms separately, the system applies big closed-loop force control method based on the zero force/torque, improving the feedback force/torque accuracy effectively. Experimental results show that self-developed 6-dof force feedback hand controller has good mechanical properties. The translational hand controller has the following advantages: simple kinematics solver, fast dynamic response, and better than 0.05 mm accuracy of three-axis end positioning, while the advantages of the rotational hand controller are wide turning space, larger than 1 Nm feedback, greater than 180 degrees of operating space of three axes, respectively, and high operation precision.

A model of motor performance during surface penetration: from physics to voluntary control

The act of puncturing a surface with a hand-held tool is a ubiquitous but complex motor behavior that requires precise force control to avoid potentially severe consequences. We present a detailed model of puncture over a time course of approximately 1,000 ms, which is fit to kinematic data from individual punctures, obtained via a simulation with high-fidelity force feedback. The model describes puncture as proceeding from purely physically determined interactions between the surface and tool, through decline of force due to biomechanical viscosity, to cortically mediated voluntary control. When fit to the data, it yields parameters for the inertial mass of the tool/person coupling, time characteristic of force decline, onset of active braking, stopping time and distance, and late oscillatory behavior, all of which the analysis relates to physical variables manipulated in the simulation. While the present data characterize distinct phases of motor performance in a group of healthy young adults, the approach could potentially be extended to quantify the performance of individuals from other populations, e.g., with sensory-motor impairments. Applications to surgical force control devices are also considered.