A study is conducted on time series data analysis relating the concept of the fractional calculus to fractals and to the fractal dimension. A new definition of the fractal dimension is provided based on a property of the fractional derivative. Using fractional Gaussian noise and fractional Brownian motion, simulations show the information content of a time series can be easily manipulated by the fractional derivative method and generated in real time.

A haptics investigation is conducted when human subjects have to deal with a bilateral teleoperation system with two levels of time delay (400 and 1,000 ms) and four types of scaling matrices that provide a passivity form of stabilization. The wave variable method was implemented to produce a controllable human-machine response. What is of interest is the resulting performance that occurs from such systems which remain passive but impacts the overall human tracking performance that can be achieved. The question addressed is how these imposed stability restrictions (via architecture constraints) may degrade human tracking performance?

The diagnostic capability of using positive and negative predictive power in dynamic and robust decision making paradigms is explored. Several mathematical formulations are discussed to employ this concept to assist in decision making when human-machine systems may have characteristics that change with time.

An important problem in computer vision is to determine the orientation of a rigid body in an image. This can be accomplished by matching points or line segments that naturally appear on the object. Several elegant and computationally fast algorithms based on the singular value decomposition and quaternions have been introduced to solve this problem. In this article, the authors first examine the important special case of identifying the attitude of 2D objects and introduce a particularly elegant solution based on the mathematical structure of the complex plane. Motivated by this simple solution to the 2D case, a new derivation of the 3D case based on the polar decomposition is presented. This derivation is in many ways more natural than previous derivations, particularly when the model and data contain no noise.

Nonlinear bistable double-well stochastic resonance systems have been successfully used for one-dimensional signal processing, based on the concept of parameter-tuning stochastic resonance. This paper investigates the applications of parameter-tuning stochastic resonance in image processing. First, a two-dimensional stochastic resonance system is introduced as a nonlinear filter for image processing. The equation satisfied by the dynamic probability density function of the images processed by this stochastic resonance filter and its solutions are then discussed. Finally, this nonlinear filter is used to process a black-white image corrupted by additive white Gaussian noise to reveal the possibility to extend the concept of parameter-tuning stochastic resonance to two-dimensional cases. This provides an innovative approach for image processing.

Time delay is a serious problem for bilateral teleoperation systems. Even a small time delay in a bilateral teleoperation system would generally degrade the system's performance and cause instability. An important approach that guarantees stability for any fixed time delay is the wave variable method. In this paper we present some recent material dealing with teleoperation systems using wave variables. In particular, we describe a wave variable scheme based on a family of scaling matrices for multiple degree-of-freedom bilateral teleoperation system. We include a derivation of a larger family of scaling matrices that guaranteed the system remains stable for a fixed time delay. A multiple degree-of-freedom bilateral teleoperation system using the new wave variable method is simulated using a SIMULINK model. In addition, the new derivation was implemented in hardware using an Immersion joystick and a C++ program

A study was conducted with haptic (forces produced on a human via mechanical systems) interfaces and how they may interact with an operator to improve tracking performance. What differs from traditional approaches is that a certain amount of random noise (in a haptic sense) was inserted into the human-machine loop. It was observed that the tracking performance of the operator benefitted from this interaction.

A fuzzy learning control technique is used for position tracking involving the vertical movement of a mass attached to a pneumatic muscle. Because the pneumatic muscle is nonlinear and time varying, conventional fixed controllers are less effective than the fuzzy controller proposed in this paper. The controller is of a PID type, with an adaptive fuzzy PD part and a nonfuzzy integral branch. A novelty of the controller is that the fuzzy inverse model, which dynamically adjusts the PD part of the controller, incorporates the internal PM pressure as an input. Experimental results are presented from the pneumatic muscle test facility in the Human Effectiveness Laboratory at Wright-Patterson Air Force Base.

The naturally-transitioning rate-to-force controller (NTRFC) is presented for remote teleoperation of manipulators. Our goal is to provide a single controller which handles free motion, constrained motion, and the transition in-between without any artificial changes. In free motion the displacement of the master device is proportional to the commanded Cartesian rate of the remote manipulator. In contact the displacement of the human operator's hand is proportional to the wrench exerted on the environment by the remote manipulator. The transition between free rate motion and applied-wrench contact with the environment requires no changes in control mode or gains and hence is termed natural. Furthermore, in contact, if the master enables force reflection, the wrench of the human operator's hand exerted on the master is proportional to the wrench exerted on the environment by the remote manipulator. This paper demonstrates the NTRFC concept via a simple 1-DOF model and then discusses experimental implementation and results from a remote Merlin manipulator teleoperated via the force-reflecting PHANToM interface.

Present virtual reality (VR) systems present powerful graphical information with human interaction capability but may be missing corresponding motion or force sensing inputs to the human operator. The concept of "virtual force" is introduced herein as a way to provide some of this missing sensing information. The "virtual force" environment is created in this paper using a displacement stick controller (joystick) with the reflective force on the controller being coordinated, in a spatial sense, with a visual scene displayed on a monitor. Force type fields are built about visual objects to provide proprioceptive feedback to the operator to improve his telepresence about the virtual scene. Since this study involves both information and control theory, certain equivalences are derived in the appendixes which extend to different plant dynamics not excluding small time delays which may appear anywhere in system. Data from a study of disabled patients and normals are presented to illustrate the efficacy of "virtual force" in terms of a performance measure related to transinformation (capacity or bits/second).>

This paper examines the kinematics of robotic wrists by using the singular value decomposition (SVD) of the wrist Jacobian. Since the manipulator Jacobian of a wrist is relatively simple, it is possible to calculate the SVD in closed form via a simple matrix factorization. Once this has been accomplished, a variety of issues can be examined including kinematic singularities and the evaluation of the manipulability and dexterity measures. These results are then applied to robots with spherical wrists and a motion simulator.>

A study was conducted to evaluate performance of a man-machine interface system consisting of a human wearing a passive exoskeleton device. This experiment obtained some crude measures of human response characteristics treating the exoskeleton device as a complicated sensor array. A Fitt's law paradigm was used to help evaluate human performance. Fitt's law is commonly used in human performance studies and it characterizes human response in terms of speed-accuracy tradeoffs that occur as humans perform tasks. Empirical data were collected during tests involving five subjects run using five levels of speed-accuracy tasks. The results are analyzed.>

A statistical algorithm is developed to study human tracking behavior in a precognitive tracking task. The algorithm presented here determines the point in time when a tracking task becomes too difficult for the human to follow. Consequently, different behavior responses are observed to occur. A decision rule based on a statistical test of normality is used to delineate the two regions of tracking behavior. The proof of convergence of this algorithm to a unique solution is given. Data from a good and poor tracker are analyzed using this algorithm to illustrate how to utilize the approach presented here.