Igor Goncharenko

Cooperative control with haptic visualization in shared virtual environments

A distributed PHANToM-based system for collaborative haptic visualization of a VR crank is presented. Physical IDOF crank model providing realistic kinaesthetic sensations of inertia and viscosity is described. Theoretical and experimental kinematic trajectory patterns are compared for the case of cooperative two-arm human movements. Nonvisual visualization applications of the system are discussed.

Modeling of human-like reaching movements in the manipulation of parallel flexible objects

The paper presents an analysis of human reaching movements in the manipulation of flexible objects. Two models, the minimum hand jerk and the minimum driving force-change, are derived and their basic features are analyzed. It is shown that the first model features two-phased hand velocity profiles, while in the second models there are multiple phases. The analysis of the phase transitions for the models considered is done in the analytical form. The results of this analysis can be helpful in the design of experimental scenarios for the verification of the theoretical models. Finally, we present some initial experimental results and analyze the applicability of the models developed in this paper

Reaching Movements in Dynamic Environments: How Do We Move Flexible Objects?

The paper presents an analysis of human reaching movements in manipulation of flexible objects. To predict the trajectory of human hand, a minimum crackle criterion has been recently proposed in literature. A different approach is explored in this paper. To explain the trajectory formation, we resort to the minimum hand jerk criterion. First, we show that this criterion matches well experimental data available in literature. Next, we argue that, contrary to the minimum crackle criterion, the minimum hand jerk criterion produces bounded hand velocity profiles for multi-mass flexible objects. Finally, we present initial experimental results confirming the applicability of the minimum hand jerk criterion in manipulation of multi-mass objects.

On the boundary conditions in modeling of human-like reaching movements

The paper deals with modeling of human-like reaching movements using optimal control theory. Typically, in the construction of optimization models, capturing the invariant features of human movements, the main emphasis is placed on the form of the optimality criterion. However, the boundary conditions are also an important part of the optimization problem. Considering reaching movements in the manipulation of flexible objects, we first show that the conventional imposition of the boundary conditions does not always produce a good match to the experimental data featuring the acceleration jumps in highly dynamic tasks. To explain the acceleration jumps, we reformulate the problem, using the concept of natural boundary conditions, and show that it improves the prediction of the experimental data. Finally, it is suggested how not only the acceleration but all the boundary conditions can placed in a natural way.

On the Influence of Arm Inertia and Configuration on Motion Planning of Reaching Movements in Haptic Environments

The paper presents an analysis of human reaching movements in the manipulation of flexible objects. Two models, the minimum hand jerk and the minimum driving hand force-change, are used for modeling and verification of experimental data. The data are collected with the haptic system supporting dynamic simulation of the flexible object in real time. We describe some initial experimental results and analyze the applicability of the models. It is found that even for short-term movements human motion planning strategy can depend on arm mass and configuration. This conclusion is based on the experimental evidence of the multi-phased hand velocity profiles that can be well captured by the minimum driving hand force-change criterion

Dynamic Model, Haptic Solution, and Human-Inspired Motion Planning for Rolling-Based Manipulation

A virtual reality haptic system for capturing skillful human movements in control of a hemisphere rolling on a plane without slipping is presented in this paper. A dynamic model of this nonholonomic rolling system with configuration-dependent inertia and gravity is derived, and a solver, required for the real-time haptic interaction, is implemented. The performance of the haptic system is verified under experiments with human subjects. Experimental data recorded by the haptic system are analyzed and some common features of human movements in the precession phase of the manipulation of the rolling system are observed. Finally, a simple actuation scheme, capturing these features, is proposed and verified under simulation.

Simple models in trajectory planning of human-like reaching movements

The paper deals with modeling of human-like reaching movements. Several models are under study. First, we consider a model of reaching movement that corresponds to the minimization of control effort. It is shown that this model is represented by the well-known Beta function. The representation can be used for the construction of fractional order models and also for modeling of asymmetric velocity profiles. The natural boundary conditions, defined in this part of the paper, can also be used in modeling asymmetric velocity profiles. Finally, we consider the minimum time formulation of the optimization problem and (for the n-th order integrator) find its analytical solution in the general form.

Optimality Principles and Motion Planning of Human-Like Reaching Movements

The paper deals with modeling of human-like reaching movements. Several issues are under study. First, we consider a model of unconstrained reaching movements that corresponds to the minimization of control effort. It is shown that this model can be represented by the wellknown Beta function. The representation can be used for the construction of fractional order models and also for modeling of asymmetric velocity profiles. Next, we address the formation of boundary conditions in a natural way. From the mathematical point of view, the structure of the optimal solution is defined not only by the form of the optimality criterion but also by the boundary conditions of the optimization task. The natural boundary conditions, defined in this part of the paper, can also be used in modeling asymmetric velocity profiles. Finally, addressing the modeling of reaching movements with bounded control actions, we consider the minimum time formulation of the optimization problem and (for the n-th order integrator) find its analytical solution.

Motor Training in the Manipulation of Flexible Objects in Haptic Environments

A system with interchangeable constraints for studying skillful human movements via haptic displays is presented. It is shown how this system can be applied to the analysis of reaching movements in the manipulation of flexible objects. In the experiment, progress in arm motor training is considered for several subjects. Experimental data are obtained for slow, moderate, and fast movements. Future applications of the system and its limitations are discussed.

Modeling and Human Performance in Manipulating Parallel Flexible Objects

Abstract This chapter presents an analysis of human-like reaching movements in manipulation of parallel flexible objects. To predict a trajectory of the human hand, a minimum hand-jerk model and a minimum hand-force-change model based on the minimization of the integral of, respectively, squared hand jerk and squared time derivative of the hand force over the movement duration are established. It is shown that within these models, the optimal hand trajectory is composed of a fifth-order polynomial and trigonometric terms depending on the natural frequencies of the system and movement time. To estimate the mass of the hand featured in the minimum hand-force-change model, a method based on following a periodic force input is proposed. A virtual reality-based experimental setup with a haptic simulator is designed, and the predictions by the minimum hand-jerk and force-change models are verified against experimental data. The theoretical predictions match the collected data with a reasonable accuracy. The experimental results show the applicability of the two considered models for the generation of human-like reaching movements in dynamic environments.