Development of a Training-Assist Robotic System Adapting to Individual Motor Abilities in Virtual Tennis Task

The present paper develops a training-assist robotic system that can adapt a reference hand motion for a virtual tennis task to individual motor abilities. The system first measures maximum hand force and velocity in reaching arm movements prior to the training, and designs a suitable reference trajectory for teaching motion smoothness and timing in the virtual tennis task based on the measured results. A quantitative index for evaluating task performance and motor functions are then defined with consideration of task dynamics. Finally, the effectiveness of the developed training system is validated through a set of preliminary training experiments with health subjects

Quantum vortex identification method and its application to Gross-Pitaevskii simulation

A method to identify a quantum vortex in a three-dimensional Gross-Pitaevskii simulation has been developed. A quantum vortex was identified by the use of eigenvalues and eigenvectors of the Hessian of the mass density, together with a condition to distinguish a point to constitute a swirling vortex from other confusing data points. This method has been verified to identify vortex axes in a Gross-Pitaevskii simulation appropriately, being useful to elucidate various statistics associated with turbulent quantum vortices. This method provides us with a unified approach to studying vortex statistics in the turbulence of both classic and quantum fluids. Our study reveals that the maximum radius of a swirling region of a quantum vortex can be as large as sixty times the healing length. The characterization of the vortex core radius relative to the healing length is reported for the first time in this paper. Furthermore, the geometrical natures of vortex axes such as the probability density function of the curvature are characterized by the healing length

Tracking Control Properties of Human–Robotic Systems Based on Impedance Control

Human–robotic systems that include interaction betweenhuman operators and robots should be designed with carefulconsideration for the dynamic property and control ability of ahuman operator. This paper performs manual tracking controltests on a human–robotic system using an impedance-controlledrobot, and investigates control characteristics of a human operatoraccording to the robot impedance properties. Experimental resultsdemonstrate that humans try to maintain dynamic properties ofan overall system as constant as possible by adjusting their ownimpedance properties. Then, a new training system using a neuralnetwork for operating a human–robotic system is constructedon the basis of the experimental findings in the human trackingcontrol properties

Analysis of Human Hand Impedance Properties Depending on Driving Conditions

This paper examines the influence of driving conditions on human hand impedance properties by using an originally developed driving simulator. A set of driving tests combining driving speed and the existence of a road centerline was carried out with five subjects. The results statistically demonstrate that humans steer a vehicle with increasing hand stiffness by activating arm muscles, i.e., under some tension, on the straight load especially at a lower speed with a centerline. In addition, it was confirmed that there was a clear correlation between steering behaviors and human hand stiffness according to the driving conditions. Human impedance measurement in driving would be useful to ascertain not only steering behaviors but also driver's physical and mental conditions for driving conditions, which may be required to develop an intelligent driving support system

The origin of MeV gamma-ray diffuse emission from the inner Galactic region

The origin of the inner Galactic emission, measured by COMPTEL with a flux of $\sim ~ 10^{-2}$ MeV cm$^{-2}$ s$^{-1}$ sr$^{-1}$ in the 1-30 MeV range, has remained unsettled since its discovery in 1994. We investigate the origin of this emission by taking into account individual sources which are not resolved by COMPTEL and the Galactic diffuse emission. The source contribution is estimated for sources crossmatched between the Swift-BAT and Fermi-LAT catalogs by interpolating the energy spectra in the hard X-ray and GeV gamma-ray ranges, as well as unmatched sources. This results in a flux of $\sim$20% of the COMPTEL excess. The Galactic diffuse emission is calculated by GALPROP to reconcile the cosmic-ray and gamma-ray spectra with observations by AMS-02, Voyager, and Fermi-LAT, resulting in a flux of $\sim$30-80% of the COMPTEL emission. Thus, we show that the COMPTEL emission could be roughly reproduced by a combination of the sources and the Galactic diffuse emission. Furthermore, combined with the extragalactic emission, we construct all-sky images in the MeV gamma-ray range to pinpoint some potential interesting targets for future missions, which would be critical for bridging the MeV gap in the spectra of gamma-ray sources.Comment: Proceedings of Science; 7th Heidelberg International Symposium on High-Energy Gamma-Ray Astronomy (Gamma2022), 4-8 July 2022, Barcelona, Spai

Bio-Mimetic Trajectory Generation Based on Human Arm Movements With a Nonholonomic Constraint

In this paper, a bio-mimetic trajectory of robots for manipulatinga nonholonomic car is generated with a time base generator (TBG).In order to reveal what kind of trajectories the robots should generatefor the given task, experiments with human subjects were performed. Ithas been shown that a human generates the trajectory with a single- ordouble-peaked velocity profile according to the geometrical conditions ofthe car. Then, bio-mimetic trajectories were generated by modeling the observedprimitive profiles with the TBG and also compared with the humantrajectories

Online Learning of Virtual Impedance Parameters in Non-Contact Impedance Control Using Neural Networks

Impedance control is one of the most effective methods forcontrolling the interaction between a manipulator and a task environment.In conventional impedance control methods, however, the manipulatorcannot be controlled until the end-effector contacts task environments. Anoncontact impedance control method has been proposed to resolve such aproblem. This method on only can regulate the end-point impedance, butalso the virtual impedance that works between the manipulator and theenvironment by using visual information. This paper proposes a learningmethod using neural networks to regulate the virtual impedance parametersaccording to a given task. The validity of the proposed method wasverified through computer simulations and experiments with a multijointrobotic manipulator

Vehicle Active Steering Control System Based on Human Mechanical Impedance Properties of the Arms

This paper presents the experimental data of human mechanical impedance properties (HMIPs) of the arms measured in steering operations according to the angle of a steering wheel (limbs posture) and the steering torque (muscle cocontraction). The HMIP data show that human stiffness/viscosity has the minimum/maximum value at the neutral angle of the steering wheel in relax (standard condition) and increases/decreases for the amplitude of the steering angle and the torque, and that the stability of the arms\u27 motion in handling the steering wheel becomes high around the standard condition. Next, a novel methodology for designing an adaptive steering control system based on the HMIPs of the arms is proposed, and the effectiveness was then demonstrated via a set of double-lane-change tests, with several subjects using the originally developed stationary driving simulator and the 4-DOF driving simulator with a movable cockpit