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.

Stability and quantization-error analysis of haptic rendering of virtual stiffness and damping

The stable, quantization-error noise-free, rendering of high-stiffness dynamics can be challenging using impedance-type haptic displays. In this paper we examine a canonical, one degree of freedom, haptic display rendering a virtual spring and damper, including the effects of the device and human dynamics, sampling, position quantization, time delay, and the low-pass filter operating on the device velocity estimate. We construct various stability and quantization-error regions as a function of the system parameters and show the necessary trade-offs that occur between them. Although we apply the quantization-error analysis to virtual spring and damper rendering, it applies to a general virtual environment. We present sufficiency for quantization-error passivity, necessity for no malicious-touch limit cycles, and necessity for no uncoupled-touch limit cycles. Using these results, aided by the presented supplementary code, we find control parameters to render the largest, renderable, virtual stiffness for a given haptic display. The analytical results are experimentally verified using a Phantom Premium 1.5 haptic device.

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

Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.