This paper investigates the vulnerability of bilat-eral teleoperation systems to perfectly undetectable False Data Injection Attacks (FDIAs). Teleoperation, one of the major applications in robotics, involves a leader manipulator operated by a human and a follower manipulator at a remote site, connected via a communication channel. While this setup en-ables operation in challenging environments, it also introduces cybersecurity risks, particularly in the communication link. The paper focuses on a specific class of cyberattacks: perfectly un-detectable FDIAs, where attackers alter signals without leaving detectable traces at all. Compared to previous research on linear and first-order nonlinear systems, this paper examines bilateral teleoperation systems with second-order nonlinear manipulator dynamics. The paper derives mathematical conditions based on Lie Group theory that enable such attacks, demonstrating how an attacker can modify the follower manipulator's motion while the operator perceives normal operation through the leader device. This vulnerability challenges conventional detection methods based on observable changes and highlights the need for advanced security measures in teleoperation systems. To validate the theoretical results, the paper presents experimental demonstrations using a teleoperation system connecting robots in the US and Japan.

Nuclei segmentation is an important pre-processing step for any vision based cytopathological diagnostic system which extracts information from nuclei to perform tasks such as cancer detection. A cell nuclei segmentation pipeline should be robust, accurate and fast. We propose a deep learning based model, Contour-Aware Residual W-Net (WRC-Net), which consists of double U-Net, [5] or W-Net. The first U-Net learns to predict nuclei boundaries and the second generates the segmentation map. Our model can accurately segment a 128x128 dimensional image in less than 0.05s. Our model can learn from a very limited training data with as low as a single training image. We tested our model on real HE (Hematoxylin and Eosin) stained cell images and it showed better overall performance against previous state-of-the-art nuclei segmentation methods.

Search-and-rescue (SAR) robots operating in post-disaster urban areas need to accurately identify physical site information to perform navigation, mapping and manipulation tasks. This can be achieved by acquiring a 3D point cloud of the environment and performing object recognition from the point cloud data. However, this task is complicated by the unstructured environments and potentially-deformed objects encountered during disaster relief operations. Current 3D object recognition methods rely on point cloud input acquired under suitable conditions and do not consider deformations such as outlier noise, bending and truncation. This work introduces a deep learning architecture for 3D class recognition from point clouds of deformed building elements. The classification network, consisting of stacked convolution and average pooling layers applied directly to point coordinates, was trained using point clouds sampled from a database of mesh models. The proposed method achieves robustness to input variability using point sorting, resampling, and rotation normalization techniques. Experimental results on synthetically-deformed object datasets show that the proposed method outperforms the conventional deep learning methods in terms of classification accuracy and computational efficiency.

Capturing clear images while a camera is moving fast, is integral to the development of mobile robots that can respond quickly and effectively to visual stimuli. This paper proposes to generate camera trajectories, with position and time constraints, that result in higher reconstructed image quality. The degradation in of an image captured during motion is known as motion blur. Three main methods exist for mitigating the effects of motion blur: (i) controlling optical parameters, (ii) controlling camera motion, and (iii) image reconstruction. Given control of a camera's motion, trajectories can be generated that result in an expected blur kernel or point-spread function. This work compares the motion blur effects and reconstructed image quality of three trajectories: (i) linear, (ii) polynomial, and (iii) inverse error. Where inverse error trajectories result in Gaussian blur kernels. Residence time analysis provides a basis for characterizing the motion blur effects of the trajectories.

The goal of this research is to develop a lower-extremity wearable link mechanism (i.e., exoskeleton robot) that is capable of reducing load against targeted body parts such as bones, joints and muscles, for shock absorption that help to support exploration of extreme environments. One of the applications of such exoskeleton is to protect a pilot of a personal vertical mobility system, or JetPack, when landing. The shock absorbing exoskeleton is to introduce series and parallel viscoelasticity to the human skeletal system. The paper presents a pilot study to validate this body-protective exoskeleton concept by analyzing kinematic and dynamic models of a human-exoskeleton coupled system based on a multi-element viscoelastic model in rheology. A proof-of-concept prototype is developed and experimental data is presented.

This paper presents a discrete switching controller for a realization of smooth pursuit. The human eye can produce both rapid and smooth movements, positioned by muscles that are a collection of quantized flexible motor units. From a control point of view, smooth pursuit can be considered as velocity matching control of an impulsive dynamical system. This may be feasible by a conventional pulsewidth modulation (PWM) controller; however, it causes high-frequency switching in each motor unit and may damage a compliant actuation system. The proposed controller generates reduced switching by optimizing a series of discrete switching commands at each primitive in an open-loop manner. This study uses a camera positioner driven by quantized compliant actuators and aims to match the velocity of a target object, while images are being captured to avoid motion blur. After images are obtained, the discrete switching controller suppresses residual vibrations to reduce switching further. Experimental results demonstrate that the proposed discrete switching controller outperformed the classical PWM controller and successfully tracked an object of interest during an exposure window.

Cytology is one of the decisive factors for the early detection of cancer. It is necessary to have a certain number of years of experience to be able to screen tumor cells for cytodiagnosis. However, this diagnosis has poor objectivity because there are so many parts that the judge’s experience and skill is responsible for. In this paper, we present a new method to extract cell nuclei from HE stained images generally used cell staining for Creation of digitized objective indicators in cytology. Our method extracts cell nuclei using combining the input image and the image previously prepared by SVM. Features used in SVM are automatically generated from CNN. Results are demonstrated by experiments using the real images and its ground truths.

This paper presents a method to generate discrete switching commands for a camera orientation system exhibiting quantization and flexibility to achieve smooth-pursuit like movements. Existing vibration suppression techniques and camera positioning devices have shown notable results but focused only on point-to-point movements. A desired motion profile can be generated by incorporating a classical feedback controller with PWM quantization but each unit actuator is required to produce high-frequency switching that can potentially damage the complaint mechanism. The proposed controller generates pulse-like switching commands for smooth-pursuit like motion to match the velocity of an object of interest. Then, switching commands for vibration suppression are generated to avoid high-frequency switching. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuator. The experiment results show that the camera orientation system successfully achieved dynamic vision given the proposed commands in an open-loop manner.

Pneumatic actuation has gained popularity in robotics, for its low maintenance, high efficiency and compactness. A recent direction is to build pneumatically driven non-magnetic platforms for robotic rehabilitation monitored by magnetic resonance imaging (MRI). Control of such systems is challenging as they involve long transmission lines to satisfy MR-compatibility requirements and direct pressure measurement at the actuator is not available. This paper presents a control algorithm that provides an accurate impedance control for pneumatic systems with long transmission lines. The algorithm involves a pressure observer based on force and displacement feedback to compensate for the lack of pressure measurement. The observed pressures are utilized in a robust controller for force tracking. The described method is tested on a system with 7 meters long transmission lines. Impedance control using the presented observer achieved stable force tracking up to 1.5 Hz, lowering mean squared error by up to %25.

This paper proposes a method for real-time de-blurring of images captured by a robotic system. De-blurring is achieved by combining a dynamics-based approach and parallel computing. Existing methods have successfully restored a blurry image but were not suitable for real-time applications. The dynamics-based method with parallel programming in the FPGA is used to estimate the PSF during the camera exposure window. The deconvolution process, which involves iterative matrix calculations with millions of pixels, is then performed on the GPU to achieve real-time performance. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuators and one vision sensor. The frame rate of image de-blurring ranges from 20.32 to 40.68 fps and thus real-time performance is achieved. In comparison to existing methods, the proposed method produces the best image quality. The dynamics-based approach is extended to real-time image stitching which is computationally cheap and robust to motion blur. It is demonstrated from image stitching that real-time de-blurring is beneficial for image processing.

Physical contact established during interaction between a human operator and a haptic device creates a coupled system with stability and performance characteristics different than its individual subsystems taken in isolation. Proper incorporation of operator dynamics in physical human-robot interaction (pHRI) conditions requires knowledge of system variables and parameters, some of which are not directly measurable. Operator endpoint impedance, for instance, cannot be directly measured in typical haptic control conditions. Several endpoint impedance estimation techniques have been explored in previous literature, based on measured kinematics and/or other correlated metrics. Arm muscle activity, measured through surface electromyography (sEMG), has been used in previous literature to estimate endpoint stiffness, which is the static component of impedance. Co-activation (co-contraction) of antagonistic arm muscles forming a pair around a joint is known to be the driving factor in modulation of endpoint stiffness. However, previous work employing muscle co-contraction to predict endpoint stiffness has mainly been absent, due in part to the inefficacy of operator models to incorporate muscle co-activation into the prediction scheme.

Force feedback haptic devices require physical contact between the operator and the machine, creating a coupled system where the stiffness changes based on that of the operator's arm. The natural human tendency to increase arm stiffness to stabilize motion increases the overall stiffness and reduces stability. Controllers commonly address this with increased damping, which slows the device and decreases operator efficiency. Previous research designed a system to estimate operator arm stiffness by measuring muscle activity and compensate accordingly, modifying the robot's motion based on operator interactions. This achieved the goal of reducing oscillations and increasing performance, but encountered drawbacks related to the unpredictable way in which humans modulate the dynamic parameters of their arm. Controllers designed to be robust to stochastic variation of system parameters are explored, and their effectiveness is validated experimentally. This could further increase the operator performance and reduce fatigue, which could translate into better efficiency and higher productivity.

With no initial angular momentum an ordinary house cat is capable of flipping over onto its feet in mid-air and landing safely after a fall. As the field of robotics advances and robots become more dynamic, control algorithms for landing safely from a long, intended fall will become more necessary. Here we present an algorithm that leverages nonholonomic trajectory planning inspired by the falling cat to orient an articulated robot through configuration changes to achieve a pose that reduces the impact at landing. The calculated impact pose results in minimal loss of energy through rolling, while maximizing the rolling time. In addition to orienting and rolling, our controller guides the system to behave like a damped spring-mass system to reduce the magnitude of contact forces. Our framework is general and is applicable to systems that can be modeled as a connected tree of rigid bodies. We illustrate the feasibility of the algorithm through simulation and physical experiments with a planar three-link robot.

Current control strategies in physical human-robot interaction (pHRI) face some limitations: endpoint stiffness level is not directly measurable in typical haptic control situations and the bilateral nature of the interaction requires proper treatment of operator dynamics. These limitations have reduced current control approaches to estimation techniques based on correlated metrics, such as electromyographic (EMG) signals. The current study investigates a parameter known to represent the nullspace of the mapping from muscle forces to joint torques in the human musculoskeletal system, i.e., muscle co-activation. It is hypothesized that this parameter is a random variable that correlates with muscle activities, measured through EMG signals. A change in this variable directly affects endpoint stiffness, and therefore system performance and stability. This study additionally presents a methodology for processing EMG (cocontraction) data prior to training a Support Vector Machine (SVM) classifier, meant to be used as a decision tool for haptic impedance control. Results presented serve as a springboard for the incorporation of a human operator model suitable for real-time implementation and sufficient to support bilateral human-robot interaction. The long-term goals of this research are to understand the mechanisms governing neuromotor adaptation in pHRI, and ultimately design a novel haptic device that tunes its impedance gains in conjunction with changes in an operator's physical and cognitive state. Such implementation would improve the efficacy of robot co-workers operated in industrial settings, among other applications.

This paper presents a new dynamics-based method for image processing in coordination with rapid ocular movement. A camera positioning mechanism with piezoelectric cellular actuators will be employed to demonstrate the effectiveness of this approach. There are a number of mechanisms for automatic camera positioning, but few have much in common with the human ocular positioning system. When a rapid point-to-point motion is created in a camera positioner, like human saccadic motion, the image sensor receives blurry images. Existing image techniques rely solely on obtained images, or use external sensors to estimate a blur kernel, or point spread function (PSF), for motion deblurring. Inspired by recent oculomotor studies, this paper proposes a method for estimating PSFs directly from the system dynamics of a camera positioning mechanism without motion sensors. The proposed method has been evaluated by using a single degree-of-freedom camera orientation system. Results are compared with conventional methods in terms of speed and accuracy.

This paper reports on the results of an experiment involving a wearable sensorimotor enhancer intended to improve tactile sensitivity in human fingertips. As briefly exposing tactile receptors to subsensory vibration is known to enhance tactile sensitivity thanks to a phenomenon called stochastic resonance in the somatosensory system, applying white-noise vibration to a fingertip is expected to improve the sense of touch and associated motor skills. Against such a background, a prototype of a wearable device called a sensorimotor enhancer is proposed here. The device is attached to the radial side of the fingertip and stimulates tactile receptors by applying vibration from a lead zirconate titanate piezoelectric stack actuator. This design keeps the palmar region free, thereby helping to maintain the wearer's manipulative ability. Sensory and motor tests involving 11 human subjects were conducted to determine the efficacy of the device, and the results confirmed its usefulness.

Piezoelectric stack actuators have the advantages of zero backlash and no acoustic noise, but their stroke is too small to actuate robotic links directly. Because the force available is often more than the required, the stroke of the piezoelectric stack can be amplified by a compliant mechanism at the expense of force. It is not always clear what the geometry of this compliant mechanism should be. Compliant mechanisms have parallels in biology in that they describe two-way interactions between the actuator and the environment. In this paper, we employ the concept of a two-port network model from circuit theory to describe this two-way interaction and present a method to obtain each element of the two-port model as an analytical function of physical geometric parameters for a wide class of geometries. This method makes use of Castigliano's theorem and Euler-Bernoulli linearly elastic beam theory. To our knowledge, this is the first two-port representation of a compliant mechanism that is based on analytical expressions of geometric parameters. This analytical model agrees well with finite-element method calculations. We also examine a representative case experimentally and achieve accuracies better than 18%.

Using successive stages, or nesting compliant amplification mechanisms, soft actuators with performance suitable for robotic applications can be constructed with piezoelectric ceramic as the active material. This paper presents a mathematical framework that describes the interactions among the various amplification mechanisms in a hierarchical nested structure. A formal treatment of nested amplification mechanisms results in two theorems that describe the stiffness properties of the whole actuator in terms of the properties of each mechanism in the hierarchy. These theorems show that the stiffness properties of the actuator can be computed by considering only the outermost few layers in the nested configuration. By virtue of this hierarchical structure, the actuator also assumes a cellular structure; it functions by summing the effects of on-off inputs coupled by a flexible connective medium. This requires a paradigm shift when selecting control strategies. A multilayer strain amplification mechanism is designed to meet the required range of travel for a biologically inspired camera positioning mechanism, and a switching control method for the actuator's 16 on-off inputs is discussed.

This paper reports the initial experimental results of a wearable sensorimotor enhancer for a fingertip. A short-time exposure of tactile receptors to sub-sensory white-noise vibration is known to improve the tactile sensitivity. This phenomenon, called “noise-enhanced tactile sensation” or stochastic resonance (SR) in the somatosensory system, is expected to enhance the sense of touch when white-noise vibration is applied to a fingertip, and thereby improve associated motor skills. A prototype sensorimotor enhancer has been developed in this research. This wearable device is to stimulate tactile receptors by applying vibration from a compact lead zirconate titanate (PZT) piezoelectric stack actuator attached at the radial side of the fingertip. This design keeps the palmar region free and maintains the wearer's manipulability. Sensory and motor tests have been conducted for health subjects to confirm the efficacy of the device. Statistical significance has been observed in most of the tests.

This paper presents the application of a piezoelectric self-sensing technique based on discharged current to robotic tweezers incorporating a rhombus strain amplification mechanism driven by serially connected piezoelectric stack actuators. Connecting a shunt resistor in series with a piezoelectric element allows it to be used simultaneously as an actuator and a sensor by measuring the current generated by the piezoelectric element. This allows the displacement and force to be measured without extra sensors or the loss of actuation capability. Applying an inverse model of the nested structure allows the force and displacement at the tip of the tweezers to be determined. The accuracy of this method is then examined by experiment for the case of free displacement.

Multiple robots can be teleoperated by a single operator to provide enhanced capacity and efficiency on accomplishing complicated tasks. The design of this kind of systems is challenging because simultaneously tele-controlling multiple robots exceeds the ability of one single operator. The intelligence and autonomy of the robots need to be integrated into the system. Besides, the communication between the operator and the multi-robot system and the communication among the multiple robots are both subject to communication constraints like time delays and packet losses. This paper designs a non-time based method to realize the single-operator-multi-robot system with random communication delay. The system is designed based on the non-time based teleoperation method and a proposed perceptive coordination method. The random delay problem and the problem of simultaneously tele-controlling multiple robots by a single operator are resolved. Experiments implemented on a multi-robot system illustrated the effectiveness of the design.

This paper demonstrates that a 1-DOF planar ball-throwing robot has the capability of controlling three kinematic variables of a ball independently: translational velocity, angular velocity, and direction. The throwing motion is modeled using two underactuated contact dynamics, called a finger-link contact model and a fingertip contact model, with a unidirectional transition from one model to another. A combination of a preliminary global search method and a search algorithm based on a simulated annealing (SA) algorithm provides joint torque commands for this highly nonlinear system. An experimental system with a 1-DOF planer manipulator has been developed that throws a disk (ball) in a frictionless plane. The experimental results confirm the validity of the contact models and the feasibility of independent control of the three kinematic variables.

This paper presents a method of modeling and subsequently characterizing stochastically controlled actuator arrays. The actuator arrays are built from cells, each containing six piezoelectric actuators and an amplification structure; however the results can be generalized to actuator arrays using solenoids, pneumatic cylinders, or any other fast acting linear actuators. The cells are controlled using an all-on all-off bi-stable stochastic process wherein all cells are given a common input probability (control) value which they use to determine whether to actuate or relax. Laying out the cells in different networks gives different actuator array properties, which must be found before the actuator arrays can be applied to manipulators. A method is provided to calculate actuator array properties such as: travel, required actuator strength/displacement, force range, force variance, and robustness for any actuator array configuration. Finally the properties of several illustrative examples are shown and a discussion covers the importance of the properties, trends between actuator array layouts and their properties, and the course of future work in the area.

This paper presents the dynamic analysis of an artificial muscle actuator designed for high-bandwidth, power-law strain amplification. The actuator is based on a nested cellular architecture of PZT stack actuators. Most smart material actuators have seen limited use in mobile robotic applications because of their small strain, low stress capacity, low bandwidth, and stringent input requirements. The proposed actuator design overcomes these limitations and can serve as a high-bandwidth multifunctional artificial muscle. The dynamic characteristics of the actuator design are derived analytically and validated experimentally. A test system mimicking flapping flight is then used to illustrate the actuator dynamics.

A static lumped parameter model is proposed for the design and analysis of nested piezoelectric cellular actuators with exponential strain amplification mechanisms. Piezoelectric ceramic material, such as Lead Zirconate Titanate (PZT), has large stress and bandwidth, but its extremely small strain, i.e. only 0.1%, has been a major bottleneck for broad applications. We have proposed a "nested rhombus" multi-layer mechanism for PZT actuators, which increases strain exponentially through its hierarchical cellular structure, for over 20% effective strain. To drive a large load, however, care must be taken in the design of the strain amplification structure. Through kinematic and static analysis this paper addresses how the output force and displacement are attenuated by the joint stiffness and beam compliance involved in the strain amplification mechanism. An insightful lumped parameter model is developed to quantify the performance degradation and facilitate design trade-offs. A prototype nested PZT cellular actuator that weighs only 15 g has produced 21% effective strain (2.49 mm displacement from 12 mm actuator length) and 1.7 N blocking force.

This paper presents a control architecture for artificial muscle materials such as shape memory alloys and polymer actuators. The active material is broken up into many small independent cells that can be regulated in a binary fashion into ON and OFF states, so that the actuator displacement is determined by the number of ON cells. In order to control the number of cells that contract, a novel closed loop feedback control method is employed. Each cell is given a small stochastic finite state machine that governs its transition between ON and OFF states. A central controller globally varies the probabilistic rate with which all of the cells make state transitions. Using this architecture, actuator displacement can be controlled in a stable, robust fashion. Different feedback laws are compared using the fixed policy value iteration algorithm to calculate expected settling time in response to a step reference. A simple law based on calculating expected future behavior is found to be very close to the optimal law computed using the value iteration algorithm. The performance of the control laws is verified on a 50 cell shape memory alloy cellular actuator.

The aim of this paper is to arbitrarily modify the load force of any selected muscle by using an exoskeleton, thus enabling "pinpointed" motion support, rehabilitation, and training. An advanced dynamic model, called a musculoskeletal-exoskeletal integrated human model, is developed. The driving-forces of the pneumatic actuators are designated by a muscle force control algorithm using the integrated model. A prototype power-assisting system is developed using pneumatic rubber actuators. The feasibility of the muscle force control is analyzed from a view point of nonlinear programming. The validity of the method is confirmed by measuring surface electromyographic signals of related muscles.

In this paper, the concept of broadcast feedback for stochastic cellular control systems is expanded to a system with nonuniform cellular length and nonuniform transition probability. The cellular control architecture was originally inspired by skeletal muscles comprising a vast number of tiny functional units, called sarcomeres. The output of the actuator system is an aggregate effect of numerous cellular units, each taking a bistable ON-OFF state. A central controller broadcasts the error between the aggregate output and a reference input. Rather than dictating the individual units to take specific states, the central controller merely broadcasts the overall error signal to all the cellular units uniformly. In turn each cellular unit makes a stochastic decision with a state transition probability, which is modulated in relation to the broadcasted error. Stability conditions of the broadcast feedback system are obtained by using a stochastic Lyapunov function. It is demonstrated that, even in the presence of the distribution of the cell length and/or the distribution of the transition probability generated in each cell, the aggregate output of the cellular units can track a given trajectory stably and robustly.

The demand for high-force and compact actuators with large strain is increasing in robotics. PZT is known as one of the promising materials for this purpose with respect to bandwidth, stress, and reliability. However, the most critical drawback of PZT is its extremely small strain, i.e. only 0.1 %. This paper presents a nested rhombus structure for strain amplification of PZT stack actuators. This structure provides a "power-law" strain amplification, resulting in over 20 % strain, which is particularly useful for gaining a large strain in a compact body, appropriate for many robotic applications. The notational convention and fundamental force-displacement analysis will be presented. In addition, the feasibility of the design concept will be addressed through the design of a proof- of-concept prototype.

A broadcast-probability approach for the coordination of a vast number of actuators is proposed. We consider an actuator that consists of many "cellular" actuator units like human muscles. Each local unit has a decision-making unit which decides whether to accept or ignore the broadcasted control signal in a stochastic manner. We demonstrate through simulation that centralized coordination is unnecessary, and redundancy and randomness of the system improve the performance

In this research, we propose a method for generating templates used for manipulation recognition that considers familiarization and fatigue. Our recognition system allows quantitative comparison of similarities among manipulations performed by observing contact state transitions on a palm surface. The system detects the contact states on the palm surface using an attached tactile sensor sheet on a manipulated object. In experiments, familiarization and fatigue are detected by measuring the variance of the manipulation. Experimental results indicate that manipulation can be divided into three periods: learning, familiarization, and fatigue. The results also indicate that variation of the manipulation becomes small when the template is generated by manipulation data during the familiarization period

In this paper, the CPG-based control method for the rotating manipulation that can adaptively change the issuing cycle of motion-triggers is proposed. The CPG model consists of the mutual inhibition network and the rotating manipulation is performed by the motion-triggers that are issued from the CPG model. The smooth change of the desired velocity can be given by the output of neurons that keep smooth increase and decrease. Experimental results using 4-fingered hand system suggest that the issuing cycle of the motion-triggers can be adaptively changed by the feedback of joint angle according to an object size.

This paper introduces a multifingered robotic hand eNAIST-Handf and a grip force control by slip margin feedback. The developed prototype finger of the NAIST-hand has a new mechanism by which all 3 motors can be placed inside the palm without using wire-driven mechanisms. A method of grip force control is proposed using an incipient slip estimation. A new tactile sensor is designed to active the proposed control method by the NAIST-Hand. This sensor consists of a transparent semispherical gel, an embedded small camera, and a force sensor in order to implement the direct slip margin estimation. The structure and the principle of sensing are described.

In this paper, a novel pointing device is proposed that utilizes the deformation of the fingertip. When a fingertip is pressed and slightly slid on a rigid plate, a partial slip, called an "incipient slip", occurs on the contact surface. While the deformation around the center of the contact area is small during the incipient slip, the boundary region moves to the sliding direction of the fingertip. The deformation changes depending on the sliding distance of the fingertip and the exerted force on the contact surface. The velocity of the pointer can be determined by the estimated distance and force based on the measurement of the deformation. In this study, the correlation between the sliding distance of the fingertip and the deformation and between the exerted force and the deformation are investigated. The degree of the deformation due to the sliding motion can be estimated based on the detected fingerprint center. The group delay spectrum tracking method is proposed for the detection of the fingerprint center. A prototype pointing device is developed to evaluate the operationality of the proposed device. Comparative experiments with conventional pointing devices are conducted. The validity of the proposed device is confirmed by the experiments.

In this paper, a grip-force control of an elastic object is proposed based on a visual slip-margin feedback. When an elastic object is pressed and slid slightly on a rigid plate, a partial slip, called "incipient slip," occurs on the contact surface. The slip margin between an elastic object and a rigid plate is estimated based on the analytic solution of a Hertzian contact model. A one-degree-of-freedom gripper consisting of a camera and a force sensor is developed. The slip margin can be estimated from the tangential force measured by a force sensor, the deformation of the elastic object and the radius on the contact area both measured by a camera. In the proposed method, the friction coefficient is not explicitly needed. The "eccentricity" is used to estimate the displacement of the elastic object at the contact area with high accuracy. The grip force is controlled by a direct feedback of the estimated slip margin. The proof of the contact stability by the proposed control is analytically given. As a result, the slip margin is maintained at a desired value, without occurring the gross slip against a disturbance traction force to the object. The validity of the proposed method is confirmed by experiments.

A number of researches for the dexterous manipulation have been studied in robotics and physiologic fields independently. Multi-fingered manipulation for dexterous robot hands should be based on analysis of human skills. The purpose of this study is to apply CPG-based control to the dexterous manipulation. In this paper, CPG-based manipulation is proposed for the rotating manipulation of the dexterous hands. Finger manipulation patterns are investigated when a subject rotates a cylindrical object. Typical contact patterns during rotating manipulation are measured by FSRs. Based on the observation, the neural circuit model which generates a similar contact pattern is constructed. The experimental results by the computer simulation suggest that rotating manipulation can be performed using the constructed CPG model.

In this paper, a grip-force control of an elastic object is proposed based on a visual slip margin feedback. When an elastic object is pressed and slid slightly on a rigid plate, a partial slip, called "incipient slip" occurs on the contact surface. The slip margin between an elastic object and a rigid plate is estimated based on the analytic solution of Hertzian contact model. A 1 DOF gripper consists of a camera and a force sensor is developed. The slip margin can be estimated from the tangential force measured by a force sensor, the deformation of the elastic object and the radius on the contact area both measured by a camera. In the proposed method, the friction coefficient is not explicitly needed. The grip force is controlled by a direct feedback of the estimated slip margin, whose stability is analytically guaranteed. As a result, the slip margin is maintained to a desired value without occurring the gross slip against a disturbance load force to the object.

A direct teaching method is effective for multi-fingered robot hand designed similar to human's hand structure. To achieve an instinctive teaching, it is necessary to perceive manipulation patterns by observing a human hand. In this paper, a perception system of human manipulation is developed as a part of direct teaching system for multi-fingered robot hand. Conventional perception systems have difficulties in perceiving complex manipulations obtained by dextrous finger actions due to the low accuracy of the CyberGlove. This paper proposes an operation measurement system using an object that is specially designed for teaching. This object consists of a six-degree-of-freedom position/orientation sensor and a tactile sensor sheet. This paper also proposes a method of spotting perception by observing a change of the contact state of the palm surface. The effectiveness of this method is confirmed by experiments.

In this paper, the global RAC-measure is proposed to a redundant manipulator mounted on a flexible body for a task-space feedback control. The tip control should be carefully designed when the dynamics of the manipulator and the flexible body are coupled such as humanoids. The measure is used to determine the redundant degrees of freedom of the manipulator based on the RAC (robust arm configuration) concept. The proposed measure evaluates the global robustness of arm configuration by mixing each RAC-measure for individual vibration mode. The redundancy of the manipulator is determined for a desired tip trajectory based on the proposed measure. As a result, a high-gain tip position control can be applied without considering the base flexibility. The validity is confirmed by a feedback-based continuous tracking for a 4 DOF human-like redundant manipulator mounted on a 3 DOF flexible body.

In this paper, the concept of the "robust arm configuration" is expanded by using a mode-shape compensator. This compensator improves the robustness of the arm configuration where the robustness is not high enough. The compensator consists of a constant gain matrix and acceleration of each joint. The structure is simple and easy to use. The design method for this mode-shaping matrix is presented, based on the previously proposed mode-shaping algorithm. Effect upon the manipulability is also examined. It suggests that inclining of the dynamic manipulability ellipsoid's principal axes by the compensator, resulting in changing the coupling rigid body dynamics, leads to the improvement of the robustness. The validity is confirmed by a numerical example and experiments. The experiments are performed with an experimental system consisting of a two-degree-of-freedom (DOF) planar manipulator and a 1-DOF flexible base. A high bandwidth positioning is realized with the obtained compensator.

This paper presents a force-reflecting teleoperation scheme with time delay. Considering reciprocal systems, the necessary and sufficient condition of the stability of the proposed type and several conventional types are analytically investigated. It is shown that the stability is not guaranteed under force feedback for a time-delayed system unless the ideal response is strictly realized, although wave transmission is applied. This problem is solved by signal filtering. The validity of the proposed type is confirmed by experiments in contacting a solid wall.

In this paper, the robustness of a manipulator mounted on a flexible base with a task-space feedback control to a fixed desired point is considered. We define the robust arm configuration (RAC), which is a special configuration where the linearized system is positive real. Lyapunov indirect method and the passivity theory guarantee a local asymptotic stability of the original nonlinear system. A finite but high closed-loop gain can be applied in the neighborhood of the RAC without considering the base flexibility, i.e., an additional sensor or a solution of whole inverse dynamics is not necessary. Considering the positive semidefiniteness of the residue matrices, a measure is proposed that measures the distance from the RAC. This measure represents the controllability of the manipulator itself, and does not depend on the underlying control law. The validity of the proposed approach is confirmed by a numerical example and experiments.

In this paper, the concept of the 'robust arm configuration' (RAC) is expanded using a mode shape compensator. This compensator improves the robustness of the arm configuration which is far out of the RAC. The compensator consists of a constant gain matrix and acceleration of each joint. The design method for this mode shaping matrix is presented based on the mode shaping algorithm. Effect upon the manipulability is also examined. It suggests that inclining of DME's principal axes, resulting in changing the rigid body dynamics, by the compensator leads to the improvement of the robustness. The validity is confirmed by a numerical example performed with a 2 DOF planar manipulator mounted on a 1 DOF flexible base. A high bandwidth settling is realized with obtained compensator.

In this paper, a novel pointing device is proposed which utilizes the deformation of the fingerprint. When the fingertip is pressed and slid slightly on a rigid plate, a partial slip, called "incipient slip", occurs on the contact surface. Since the deformation around the center of the contact surface is small, the center of the fingerprint can be detected during the incipient slip. The group delay spectrum (GDS) tracking is utilized to detect the center of the fingerprint. The velocity of the pointer is controlled by the changes of the contact area on the basis of the tracked center. A prototype pointing device is developed to examine the operationality of the proposed method. The experimental results show that an operator can control the pointer with high accuracy.

In this paper, the role of the human being toe is investigated. The change of the sole pressure distribution using a sole pressure distribution measurement system and that of the toe pressure using a toe pressure measurement system at walk by the existence of a toe are investigated. In order to investigate the change of the whole walking, the affection of a walk posture using a 3D motion capture system by the existence of a toe is also measured. Furthermore, the change of the amount of energy consumption at walk by the existence of a toe is measured by a spirometry system. At last, we investigate the roles of the toe, such as, the efficiency of the big and 2nd toe, and the stabilization of the posture, by the synthesis of these results.

We consider the robustness of a manipulator mounted on a flexible base with direct positioning error feedback control. Based on the positive realness of the transfer function matrix, we define the robust arm configuration which is a kind of singular configuration where the system is passive. We show that the system shows good robustness in the neighborhood of this robust arm configuration. We propose a measure which indicates the distance from the robust arm configuration. We also show that the robustness is closely related with the robust stability margin by the normalized coprime factor description. The validity is confirmed by numerical examples. The method is applied to a flexible assembly system consisting of a manipulator and two moving tracks.

The flexibility of the mechanical system is one of the factors of the bandwidth limitation. Especially, it is known that an out-of-phase vibration mode makes the closed loop unstable with the negative feedback of the positioning error. In this paper, a novel mode shaping method for in-phase design of flexible structures is proposed. From the relation between the modal analysis and the state-space representation, we classify in-phase mode shaping into two types based on the boundary which is passed across during the shaping process. By the proposed method, the out-of-phase modes are shaped into in-phase in order of the natural frequencies applying a task priority based modification scheme. We also propose a method of selecting the boundary, so that the vibration mode is shaped into the arbitrary type of in-phase design.

Time delay usually makes master-slave systems unstable, even if the system is stable under no time delay. In this paper, we propose a control scheme for master-slave systems with time delay which maintains stability defined by scattering theory. We define four types of realization of the ideal response and describe control schemes which strictly realize the ideal response. Based on these schemes, we propose a practical control scheme and its stability is proven. We also discuss stability of conventional schemes, and show that they cannot maintain stability. Finally, some experimental results are presented.

A three-dimensional (3-D) process simulator, OPUS/3D, has been developed. It has access to two-dimensional (2-D) process simulation results. Impurity profiles and structural data simulated rigidly in 2-D space are expanded to 3-D space at an arbitrary stage of the simulation processes. 3-D simulation follows until the end of the process. The access to 2-D simulation results enables OPUS/3D to handle curved boundaries as seen in field oxides. OPUS/3D has three different methods for expanding 2-D results. Errors due to these expansions are discussed. OPUS/3D was applied to 3-D simulations of MOS devices at the corner edge of the active region and in the channel region near the source/drain. Computation time was drastically reduced by replacing part of the 3-D simulations by 2-D simulations. Some 3-D effects are confirmed by OPUS/3D.>

A general-purpose two-dimensional process simulator OPUS (Oki Process simulator for ULSI Structures) for arbitrary structures is discussed. By separating a preprocessor from a main processor, OPUS can simulate any kind of impurity or material with up to eight impurities and ten materials. OPUS utilizes a finite-difference method for diffusion analysis without any coordinate transformation. In order to minimize errors due to discretization around the curved boundaries, OPUS has introduced two kinds of boundaries. The first is true boundaries by strings. The other is quasi-boundaries formed through simplifying but retaining the shape of true boundaries as long as possible. The quasi-boundaries and resulting dummy cells are used for discretization of the diffusion equation. General features of OPUS are first introduced with special emphasis on dummy cells. Errors caused by dummy cells are discussed. The capacity of OPUS is then demonstrated through application to a trench process and to a full MOS process with a sidewall.>