In recent years, the number of people complaining about inappropriate sleeping habits has been increasing annually, and non-contact measurement of vital signs during sleep has attracted attention. A non-contact heart rate measurement method using an infrared camera was developed. However, camera-based heart rate estimation is problematic because motion artifacts significantly impact measurement results. The conventional method combines multiple heart rate estimation methods or makes appropriate peak selections using the coordinates of the facial image to perform heart rate estimation that considers motion artifacts. However, motion artifacts are caused not only by changes in facial position but also by changes in angle. Conventional methods cannot properly remove body motion, which affects the heart rate estimation system. Therefore, this study proposes motion artifact removal by combining an adaptive filter with singular spectrum analysis. Additionally, the Euler angle information of the head extracted using a convolutional neural network was incorporated as a parameter to estimate the heart rate corresponding to the motion artifacts caused by angular displacement. The estimation accuracy was demonstrated through the experimental results.

Abnormal breathing in daily life can be indicative of various diseases. Daily measurement of breathing rate enables the early detection of diseases and rescue of patients in severe cases. Wi-Fi, which is widely used in day-to-day life, is a suitable sensing method for daily measurements. Accordingly, a breathing rate estimation method using the Wi-Fi channel state information (CSI) was developed. In the conventional method, an accuracy of up to 99% was achieved in the estimation of breathing rates for singular individuals. However, this accuracy is insufficient for multiple individuals owing to the interference of vital signals obtained from CSI. Therefore, this study proposes a multi-person breathing rate estimation system that suppresses vital signal interference. To estimate the breathing rate of multiple people, the proposed method employs Tucker decomposition to decompose vital signals from the CSI. The processing speed and accuracy were improved using the proposed method. Finally, the effectiveness of the proposed method was demonstrated through experiments.

In recent years, population aging in developed countries has become an increasing problem, and labor shortages in the transport industry have become an issue. Human-robot interaction (HRI) is expected to address this problem. Admittance control, an HRI method, is a useful control technique for reducing the burden on humans. However, the vehicle may behave dangerously if the wheels or body collide with an obstacle, or if a sudden large force is applied by a human. This behavior is due to the windup caused by motor torque saturation and reduced tracking performance of the admittance controller. To address this problem, admittance control that considers torque saturation was developed. In this study, a power-assisted control system was constructed using admittance control. The usefulness of the proposed method for tracking performance degradation was demonstrated via numerical simulation. The root mean square errors (RMSE) of the error between the reference and response velocities were compared between the proposed method, the anti-windup method, and standard admittance control. It was confirmed that the RMSE of the proposed power-assisted system was the smallest and that a reduction of approximately 99% could be achieved compared to the standard admittance control-based power-assisted system.

Surface-mounted permanent magnet synchronous motors (SPMSMs) are used in various fields because of their high efficiency and high power density characteristics. Because they are generally driven by vector control, a type of current control, the position of the rotor must be detected. Rotor position detection is generally achieved by attaching an encoder or resolver to the exterior of a motor. This inevitably increases the volume and weight of the exterior of a motor. Although sensorless methods are available for determining the rotor position, their detection accuracy is low and it is difficult to acquire stable position information over the entire speed range. An embedded magnetic absolute encoder, which detects the rotor position by observing its magnetic flux, can acquire the rotor position without requiring the need for an external position sensor. However, calculating the absolute angle when two or more SPMSM pole pairs exist is difficult. This study proposes an embedded magnetic absolute encoder in an SPMSM that can calculate absolute angles. The proposed SPMSM enables the calculation of absolute angles using permanent magnets with different magnetic flux densities.

In recent years, owing to the implementation of advanced safety technologies, there has been a reduction in the number of automobile accidents. However, traffic accidents caused by human error, such as driving inattentively or while drowsy, are occuring more frequently. To address this problem, automated systems that detect whether a driver is drowsy have been developed. Typically, such systems use electrode-type sensors to acquire electroencephalogram or electrocardiogram readings and perform in-cabin monitoring using cameras. However, wearing such sensors involves some discomfort for the driver, and these cameras are susceptible to noise; moreover these systems generally record personal information such as the driver's face. In this study, we propose an estimation system using heart rate variability (HRV) features acquired using noninvasive devices that cause less restriction on the driver's movement. Our proposed system obtains biometric information from gyroscopes attached to the driver's seatbelt and derives features indicating HRV. Additionally, we have trained a random forest classifier to detect drowsiness as this approach showed relatively high accuracy in prior studies. The results of an experimental evaluation confirm that the proposed system achieved an accuracy of 85.4 % in distinguishing between wakeful and drowsy states. We used the Karolinska Sleepiness Scale (KSS) to validate the results of the estimations. Our method can obtain biometric data without using invasive sensors or substantially restricting the driver's movements, and the random forest model can distinguish sleepiness.

In this study, we developed a novel magnetic absolute encoder with different magnetic flux densities. Magnetic encoders can be created with a simple structure consisting of a magnet magnetized in a sinusoidal shape and a sensor that detects the magnetic field. They are known for their compact design and excellent environmental resistance. A method of obtaining even higher resolution signals while maintaining absolute accuracy is to use a magnet with different magnetic flux densities and Hall sensors. However, there are physical limitations in improving the accuracy of a multi-polarizing magnet with different magnetic flux densities. In this study, we developed a magnetic encoder with a new structure using a magnet with different magnetic flux densities and anisotropic magnetoresistive(AMR) sensors. The developed system can calculate the absolute angles and output angular frequency signals twice as high as those of AMR sensors, thereby improving the resolution without requiring a multipole magnet. In the past, distortion was considered to occur because AMR sensors were used outside the saturation sensitivity region to capture the amplitude characteristics of a magnet with different magnetic flux densities; however, this was solved by correction using a look-up table. Finally, an actual device was created and validated by comparing the measured values obtained in the experiment with those obtained using a Hall sensor.

In recent years, motor technology has been utilized in a wide range of fields, such as robots and automobiles. When a motor is used for electric vehicles, it is required that the motor supplies different levels of torque in different situations. For example, a motor in an electric vehicle is required to generate a higher torque when the electric vehicle suddenly stop. The braking distance can be shortened by improving the maximum torque of the motor, at the time of a sudden stop.Conventional motors have a larger safety margin of heat-resistant to avoid the motor from breakage. Therefore, it is not possible to provide the maximum torque that the motor originally has. The purpose of this research is to increase the maximum torque of the DC motors. A temperature estimation formula was used to set parameters for each current value to be supplied to the motor. We measured the actual temperature of the motor and compared the measured value to simulation value that is calculated with MATLAB/Simulink to reduce the difference in temperature between measured value and simulation value within 5◦C. Furthermore, we built and implemented a current control algorithm that incorporates the temperature estimation for this motor, so that a larger current can be supplied to the motor as compared with conventional motors. As a result, the maximum torque of the motor can be improved by 5.5 times.In addition, because a high-speed response is required to avoid emergency situations in automobiles, optimal feedforward control in real time was performed.

Encoders are the most commonly used position measurement sensors in industrial machines and robots. Compared to potentiometers, encoders have advantages in terms of environmental resistance and cost, and their detection speed and resolution are comparable to those of potentiometers, so the use of encoders in the field of precision positioning continues to expand. Since the accuracy of motor control depends on the accuracy of angle and angular velocity obtained from the encoder, encoders with high reliability and high accuracy are required. The authors have developed a high-resolution and high-accuracy absolute rotary encoder that applies eccentric rotation. However, eccentric rotation causes vibration due to disproportionate force, which may lead to deterioration of accuracy and lifetime.In this paper, we proposed a new angle calculation method that calculates the absolute angle from the signal characterized by the use of magnets with different magnetic flux densities. With the proposed method, the absolute angle is obtained with the same accuracy as the conventional method.

Motor is important device that support the foundation of our lives. For high-precision control of robots, it is necessary to improve the accuracy of the encoder, which is a position sensor. High resolution can be achieved by using multi-pole magnets. However, the absolute angle is lost. In the previous research, eccentric rotation was used to achieve high resolution without loss of absolute angle. But the number of sensors to be used increases for higher resolution by further increasing the number of poles. When the number of sensors is reduced in relation to the number of magnetic poles of the magnet, a large angle error will occur. In this paper, we proposed a method to calculate the angle when the number of sensors is reduced by using Long Short-Term Memory. The proposed method reduces the large angle error when the number of sensors is reduced.

Monitoring vital signs is critical for daily health management and early detection of diseases. In this paper, we introduce a system for measuring the respiration rate and heart rate with high accuracy using channel state information obtained from commodity Wi-Fi. Unlike conventional methods, this system achieves high accuracy by separating biometric information from the signal using variational mode decomposition, which filters adaptively. By testing this system in an indoor environment, we achieved an accuracy of 98.5% for respiration rate and 98.5% for heart rate.

In recent years, robots to replace human labor in industrial fields and extreme environments are required. Especially, teleoperation technologies are expected to play an important role. Therefore, this study proposes bilateral haptic feedback control for different working ranges based on force-information transmission. Conventional bilateral control systems for the different working ranges are based on a dimensional scaling method which utilizes position/velocity-forces hybrid control. In dimensional scaling, the position of the master system tracks the speed of the slave, and the velocity of the slave system tracks the position of the master system. The proposed method can achieve a dimensional scaling control with force feedback by transmitting only force information with the performance equivalent to the conventional method. The proposed method can reduce the amount of haptic data traffic because of the utilization of only one type of information. Simulations evaluate the proposed method with a comparison to the conventional methods.

When performing tasks using deep learning, the quantity and quality of data are important. However, in unsupervised anomaly detection, it is difficult to obtain a large amount of high-quality training data. Hence, data are typically extended via rotation, translation, and cutting. However, the typical data augmentation method may generate data far from the original image. To obtain various high-quality training data, we partially use AugMix, a data augmentation method that mixes the original image with images obtained via image processing, such as by rotating the original image. Using this data augmentation, new data can be generated while retaining the features of the original image as much as possible, and the diversity of training data can be enhanced, compared with performing the same image processing. Consequently, the effectiveness of the proposal method for improving the accuracy of unsupervised anomaly detection is confirmed.

In recently, the number of traffic accidents caused by automobiles is on decreasing trend, but caused by drivers, such as dozing driving, has increased, relative to the number of traffic accidents. Many studies report that drowsiness occurs during driving, and development of a system to sense quickly from the viewpoint of automobile driving support technology is required. In this research, the authors developed a biometric measurement system adopting capacitive coupled electrodes which can be sensed by the driver unconsciously and under unconstrained condition. In this paper, the authors explain the measurement principle using capacitive coupled electrodes, digital filter, RRI detection algorithm, body movement detection and this interpolation algorithm in Real-time. The authors have conducted RRI measurement experiments using the proposed system and showed that it is possible to measure RRI with high accuracy even when compared with highly reliable physiological measurement systems.

Recently, accidents relating to automobiles have been decreasing due to the development of advanced safety technologies for automobiles and the legal system for dangerous driving. However, the ratio of traffic accidents caused by human errors such as careless and dozing driving in the whole car accidents have been increasing. There has been a requirement for developing sleepiness detection system promptly. In this research, the authors propose a method of estimating driver sleepiness in a car using biological information. The driver while driving is trying to stay awake, fighting against sleepiness that affects the physiological index. By using this index, the authors made sleepiness estimation formula and conducted evaluation experiments. The results show that the sleepiness estimation rate is improved in comparison with a conventional method. It suggests the usefulness of the proposed method.

This research proposes a force control for a vehicle robot with an inverted two-wheeled/stable traveling mode. The conventional inverted two-wheeled vehicles have advantages such as the capability of pivot turn compared to the vehicle robots with three or four wheels. Additionally, if an arm (manipulator) is mounted on the vehicle, multi-functionalization of the mobile robot is expected. However, the inverted two-wheeled vehicles have disadvantages such as statical instability and deterioration of the main tasks and inverted-pendulum control due to mutual interference because of the presence of the underactuated joint. Therefore, this research proposes a force control as one of the multi-functionalization by a mobile robot with the advantages of both two-wheeled and stable traveling mode. This research introduces a variable compliance control for the pitch angle direction, which enables the flexible and stable transition between a two-wheel mode and stable traveling mode. The proposed method realizes a stable contact motion to the environment with achieving a soft landing and stable inverted traveling movements at the transition from the two-wheel mode to three-wheel mode. The simulations evaluate the proposed method.

The human brain has two states, i.e., a sleep state and an awake state. Human beings live by circulating these two states in a well-balanced. If the transition from an awake state to a sleep state or from a sleep state to an awake state becomes difficult, balance is lost, and sleep disorder occurs. Therefore, the way to control the transition between awake and sleep states smoothly is needed. In order to shift the sleep state and awake state bidirectionally, this study uses vibrations as a method to promote the transition of sleep state and awake state with minimum invasion to the body. In this study, a vibration is generated based on the music that subjects felt healing and awakening, and is evaluated by giving vibration and sound to subjects with a massage chair. As a result, it turned out that the effect of the vibration corresponds to the impression of music which subjects receive. Also, it is found that personal favorite music enhances the healing (or awakening) effect of the vibration.

Drowsy driving will lead to a serious accident because the operation of the car becomes impossible. In order to prevent such accidents, Development of a drowsy driving prevention system is necessary. Therefore, this research uses eye movements that are correlated with high sleepiness and mouth movements that are said to be correlated with waking effort. In addition, the authors use Web camera and Dlib to measure these parameters in real time. Furthermore, in order to measure blinks, the authors implemented a blink measurement method corresponding to noise caused by body movement. In addition, the authors have proposed a sleepiness detection method using the acquired data. The control engineering method was used in this method. As a result, the accuracies are 90% for the blink measurement method and 91.7% for the drowsiness detection method.

Recently, a field of the servomotors is enlarged in robotics, automobile, and medical applications. In addition, requirements of the servomotors have been changed. Among them, demands of motors for downsizing, high accuracy and high functionality are increasing. However, it is difficult to achieve downsizing of the sensors for controlling the motor and the high accuracy and intelligent functions simultaneously. Therefore, the authors propose a magnetic encoder with realizing small size and high precision. This sensor can easily achieve reduction of the size and high resolution. The accuracy of the encoder can be doubled compared with the conventional structure by changing the number of poles of the magnet from the two poles to the four poles. However, it becomes difficult to detect the absolute angle by the conventional method. Therefore, the authors use the eccentric rotation of the sensor magnet, for the novel absolute angle detection methods. This research describes the new method of calculating the absolute angle and the experimental results for the accurate measurements of the magnetic absolute encoder. Accuracy of the developed magnetic encoder reached 14-bit. The proposed structure realizes the absolute angle simultaneous detection.

Recently road accidents caused by drivers falling sleep has been increasing among other car accidents. Many studies report that drowsiness occurs during driving, and it is required to develop the driver drowsiness detection system. In this study, the authors use capacitive coupling electrode sensors that enable sensing the condition of a person while driving a car without physical constraints and even being unaware of the device. This paper explains about the measurement principles of capacitive coupling electrodes, the configuration of analog circuit, and a digital filter for R wave detection algorithm using a microcomputer are described. Thereafter, experiments to prove the created system can measure the RR interval are described. Further, it is shown that the RR interval measured by the system is as accurate as a cardiograph equipment electrocardiograph.

In this research, the authors investigate vibration stimulations as one of the healing environments and examine whether the vibration stimulations has the healing effects. First, the three types of vibration are compared. Among them, the vibration of which the amplitude is modulated had the highest healing effect, but it was found that the healing effect is reduced if the vibration continues to be given for a long time. Next, focusing on the 1/f fluctuation. It is found that the vibration of the sea wave sounds with 1/f fluctuation has the continues to have healing effect even if it continues to be given for a long time. Finally, it is found that there is no healing effect if vibration of the rock drilling sounds without 1/f fluctuation. However, it is found that the vibration with 1/f fluctuation generated based on rock drilling sound has a healing effect in contrast. Therefore, it was found that the vibration with 1/f fluctuation influences the healing effect.

The six papers in this special section focus on the use of advanced mechatronics in research and industrial applications. Mechatronics has evolved during the last few decades to become well recognized as a philosophy of design and an engineering discipline. It has emerged through the philosophy of concurrent design of mechanics, electronics, and computer of a system for an integrated and efficient approach to system design. Most universities nowadays offer a degree in mechatronics. This stems from the fact that as technology progresses, the traditional barriers between engineering disciplines are dimensioning. Mechatronics evolution went through many stages to reach its current advanced stage.

This paper studies the feasibility of privacypreserving data mining in epidemiological study. As for the datamining algorithm, we focus to a linear multiple regression that can be used to identify the most significant factors among many possible variables, such as the history of many diseases. We try to identify the linear model to estimate a length of hospital stay from distributed dataset related to the patient and the disease information. In this paper, we have done experiment using the real medical dataset related to stroke and attempt to apply multiple regression with six predictors of age, sex, the medical scales, e.g., Japan Coma Scale, and the modified Rankin Scale. Our contributions of this paper include (1) to propose a practical privacy-preserving protocols for linear multiple regression with vertically partitioned datasets, and (2) to show the feasibility of the proposed system using the real medical dataset distributed into two parties, the hospital who knows the technical details of diseases during the patients are in the hospital, and the local government who knows the residence even after the patients left hospital. (3) to show the accuracy and the performance of the PPDM system which allows us to estimate the expected processing time with arbitrary number of predictors.

In many hospitals, data related to patients are observed and collected to a central database for medical research. For instance, DPC dataset, which stands for Disease, Procedure and Combination, covers medical records for more than 7 million patients in more than 1000 hospitals. Using the distributed DPC data set, a number of epidemiological studied are feasible to reveal useful knowledge on medical treatments. Hence, cryptography helps to preserve the privacy of personal data. The study called as Privacy-Preserving Data Mining (PPDM) aims to perform a data mining algorithm with preserving confidentiality of datasets. This paper studies the scalability of privacy-preserving data mining in epidemiological study. As for the data-mining algorithm, we focus to a linear regression since it is used in many applications and simple to be evaluated. We try to identify the linear model to estimate a length of hospital stay from distributed dataset related to the patient and the disease information. Our contributions of this paper include (1) to propose privacy-preserving protocols for linear regression with horizontally or vertically partitioned datasets, and (2) to clarify the limitation of size of problem to be performed. These information are useful to determine the dominant element in PPDM and to figure out the direction of study for further improvement.

In recent years, energy management of the mobile device is researched in two approaches; energy saving and energy charging. In terms of energy charging, though the wireless charging and the energy harvesting technologies have been proposed, these technologies could not satisfy all of the criteria; location-free, connection-free, reliable and human-safe. In response, the authors are proposing a new energy management method for mobile device based on the Wireless Charging Robot (i.e., mobile robot with wireless charging function via magnetic coupled resonances). It operates in the combination of two charging tasks; charging the mobile device from robots (i.e., mobile device charging task), and charging the robot from charging stations connected to power system (i.e., self charging task). In this manner, robots mediate the energy delivery from the power system to the mobile devices, and consequently, the system satisfies all of these criteria. This paper introduces the abstract architecture and procedure of the overall system with the basic method for designing the wireless charging function in the energy management system.

Recently, various types of mobile robots have clearly gained attention and some are readily available. In response to this, the authors have been studying on realizing both wireless charging and self-localization as an integrated compact system using magnetic resonance coupling. However, due to the fact that sensing range depends on the fixed quality factor of antenna, the narrow sensing range of the current system was a problem in the practical use. Therefore, the authors are considering a new method which enables the control of the sensing range by active quality factor control. However, the introduced theory and simulation results were preliminary so far. In response to this, this paper introduces an advanced sensing algorithm for overall sensor system with the experimental results of the prototype setup. As a result, it was proved that the quality factor could be controlled with the proposed method.

Representing occlusion between real objects and virtual information in augmented reality is essential. However, since existing researches on handling occlusion at augmented reality required cameras embedded in display device, the computational load of the device was very high and camera less display device couldn't represent occlusion. In this paper, we propose an approach for representing occlusion at augmented reality system in Intelligent Room where display devices don't need a camera and high throughput.

In recent years, various types of wireless power transmission method have been proposed. However, assuming the mobile devices in the living space as a target, the traditional methods seem to be ineffective. The only wide range transmission method based on electro-magnetic wave has the problem of the safety to humans, while the effective range of the other transmission methods are too short. Therefore, a new wireless power transmission method called Energy Logistics is proposed in this paper. The method realizes safe and wide range power transmission by the combination of mid-range energy coupling technique and energy delivery robot. The energy delivery works as a substitute for power cable between the power source and the mobile devices, while the energy coupling is used for connecting power source and energy delivery robot or energy delivery robot and mobile device. Basic characteristics of mid-range wireless charging for lithium-ion battery via magnetic resonance coupling is derived since it is the challenging task in the Energy Logistics. Furthermore, some approach for increasing the transmission efficiency together with realizing the suitable charging power and voltage is discussed.

In recent years, lack of sleep is becoming a serious problem in modern society since it causes accident, overwork death and depression. Among the several factors, difficulty getting to sleep is one of the big reasons. In this paper, sleep-promoting robot is proposed as an aid to this problem. The basic concept of the robot it to shorten the sleep-onset time by giving two types of external stimulation, sleep-promoting method giving vibratory contact pressure based on respiratory waveform during sleep and sound stimulation characterized by heart rate variability during sleep to the human. Therefore, the proposed robot could be better choice as the solution of insomnia compared to current methods since it has a possibility of promoting sleep in the short run, convenient and not swallowing the pills. The paper presents not only the concept of the proposed sleep-promoting robot but details such as evaluation method and experimental setup configuration. Here, comparison of the sleep-onset time and comparison of the time change in sleepiness are proposed as evaluation method. Electroencephalograph is selected as the measuring equipment since it is possible to quantify the sleepiness. The appearance of the robot is decided to be pig-like since it correspond the condition of having the image of cuteness and the rarity in the daily life at the same time.

This paper presents the social behavior of a physical agent in intelligent space. Intelligent Space (iSpace) is a space in which many intelligent devices, called distributed intelligent network devices (DINDs) and including not only sensors but also actuators, are installed. Robotic devices, which provide services to users, are considered as physical agents in iSpace. For facilitating long-term communication between users and a robot, we focus on building a social relationship between a user and a robot. Toward this end, a methodology for designing social behaviors of the robot is required. Therefore, we have used an ethologically inspired approach to construct a robot behavioral model for an iSpace-based elderly monitoring support system. In this paper, the robot behavioral model is presented and implementation of robot behaviors is discussed.

To maintain long-term human-robot communication, a robot behavior model based on the behaviors of dogs in human-dog relationships has been proposed. We apply this model to a robot in a monitoring support system designed for home care. This paper presents an improvement to the model, adding behavioral factors to show different characteristics of the behaviors. We conduct experiments to evaluate users' impressions of the robot behaviors when given different characteristics using a simulator. Our findings show that the subjects had the impressions that we expected based on the factors selected.

This paper presents an exploratory behavioral model for human-robot communication based on an ethological approach. To maintain long-term human-robot communication, building social relationships between the user and robot is important. As a model of social relationships between different species, we focus on human-dog relationships. We apply dogs' behaviors observed from the stranger situation test as a base model of the robot. Exploratory behavior is one of the dogs' behaviors. In this paper, human-robot communication is considered for the purpose of home-care support. For this purpose, an exploratory behavior model for home-care applications is proposed.

Abstract This article describes a node capacitated in‐tree packing problem. The input consists of a directed graph, a root node, a node capacity function, and edge consumption functions. The problem is to find the maximum number of rooted in‐trees, such that the total consumption of in‐trees at each node does not exceed the capacity of the node. The problem is one of the network lifetime problems that are among the most important issues in the context of sensor networks. We establish the computational complexity of the problem under various restrictions on consumption functions and graphs. For example, we consider general graphs, acyclic graphs, and complete graphs embedded in the d ‐dimensional space \input amssym ${\Bbb{R}}^d$ having edge consumption functions depending only on distances between end nodes. © 2011 Wiley Periodicals, Inc. NETWORKS, 2012

In this paper, an accurate long-distance position measurement system using laser range finders (LRFs), which can be used for surveys in construction fields is proposed. Since the LRF is a sensor which can measure distance to surfaces of objects by radiating laser beams from itself and receiving the reflected ones, data obtained from the LRF are nothing more than the contours of objects. For this reason, we adopted cylindrical shaped objects since the contour, a circular arc, is invariant against rotation. Therefore, this research aims to fit circles to the arc-shaped contours of the cylindrical objects and estimate their accurate center positions by applying the least square method and maximum likelihood estimation. If we know the radius of the cylindrical object in advance, the aforementioned two methods become non-linear problems. For this reason, we applied the Newton-Raphson method to solve these non-linear equations. We improve the angular resolution of the LRF by using a pan unit, and reveal that the maximum likelihood estimation can give us the most accurate center position. Additionally, we implemented proposed position measurement system in an actual construction field.

We have proposed the spatial memory which is a human interface to operate iSpace agents such as mobile robots, computer displays, etc. Spatial memory enables users to store computerized information ranging from digital files and commands for robots in real space by assigning digital information to a three-dimensional position. Users can retrieve the information by pointing the locations using their own bodies directly. The accessed information will be delivered to a suitable iSpace agent who should execute it. We named information arranged into real space ldquoSpatial-Knowledge-Tagrdquo (SKT). In order to encourage people to share useful information via spatial memory, they need to retrieve pre-arranged SKTs which are arranged by somebody. In this paper, firstly we show possibility of finding SKTs through seeing other users' actions, but not using any display to show locations and content types of SKT. Then, we present two kinds of displays to show users locations and content types of SKTs. Specifically, one is a visualization using computer graphics (we call ldquographical displayrdquo), the other is a display using vibration (we call ldquovibration displayrdquo). Experiments to compare the efficiency of the methods to find SKTs are shown.

In this paper we present a method for estimating the position of mobile robots using a combination of both robot’s onboard sensors and sensors at fixed locations in the environment, where we use laser range finders as sensors. This is a situation which arises in so-called Intelligent Spaces, where there are both static sensors and mobile robots present. The method we present extends the robot localization methods based on occupancy grids, however here occupancy grids are used to represent not only the geometry of the environment but also that of the robot. For tracking the robot we employ a particle filter. The details of the method are given and experimental results are shown to illustrate the method.

This paper presents the nanorobotic resistance spot welding (RSW) of ultra-thin film three-dimensional helical nanobelts(HNBs) for the assembly of nanoelectromechanical systems (NEMS) from as-fabricated building blocks. Three-dimensional HNBs with metal pads firstly placed onto as-fabricated micropipette electrode. using nanorobotic manipulation, then fixed with RSW. The spot-welded structures are then electro-mechanically characterized to show the ohmic conductivity and electromechanical stability. Experiments show that RSW can enable stable ohmic contacts with sufficient mechanical strength for constructing devices such as force sensors from HNBs.

This paper describes an observation system of human-objects interactions to extract relations among humans and physical objects in Intelligent Space (iSpace). The purpose is to obtain information of physical objects which can not be described in advance, in other words, depends on usage history of individual users. It is important issue for the iSpace to recognize human activities and design services for humans. In this paper, a method for multiple objects localization in the Intelligent Space is presented. The localization is realized by using two types of information. One is acceleration data which is used to determine whether an object is being operated. Acceleration data is acquired by using sensor network system. The other is hand position information of a nearest user to one object. By combining the information, positions of objects are able to be estimated by corresponding positions of user hands. In this method, determination of objects initial position is a first problem. In order to solve it, we use correlation of acceleration data among user hands and objects. Initial position of each object is given based on user’s hand position which is scored high correlation.

Users cannot search information by mathematical formulas as queries in existing search engines. This is because mathematical formulas are not expressed as a sequence of characters. Some formulas are expressed in a complex structure like fractional numbers and index numbers. We present a search engine for MathML objects using the structure of mathematical formulas. The system makes the inverted indices by using the DOM structure of the MathML object. We proposed two types of index. One type is constructed from some paths of the DOM structure and expressed in XPath. The other type is constructed by encoding the nodes in the same level in DOM structure. This paper describes the experiment conducted to study the effectiveness of those indices by using the mathematical contents which are open to the public on the Internet.

This paper presents a classification of human activities based on usage history of the spatial memory system and a numerical expression of each human activity in order to estimate individual human's intended purpose of an environment. We named the intended purposes for a place "space-human activity association". Intended purposes for a place will be different depending on the purpose of activities, even if observed activities are almost the same. Therefore, estimation of space-human activity association is important for intelligent environments to design services provided for individual human according to his/her current situation. The spatial memory system enables human users to store computerized information into the real world by assigning a three-dimensional position to the information, and to retrieve the information by directly indicating the point using their own hands. In the spatial memory system, what associates computerized information with a three-dimensional position is called "spatial-knowledge-tag (SKT)". The users actively create SKTs based on their need. As a result, arranged SKTs in a specified environment correspond to activity histories of the users. Also, users' intended purposes for the environment are reflected in the arrangement. Therefore, classification of arranged SKTs leads to classification of human activities, and accordingly estimation of intended purposes for places. In this paper, we describe two approaches to classify human activities. More specifically, the first approach is a classification of arranged SKTs by using only SKTs' information. The second approach is a classification of arranged SKTs by using both SKTs' information and usage history of the spatial memory system. As a result, the classification based on usage history of the spatial memory system showed multiple activities in the same area. On the other hand, the first approach resulted in a single cluster in the same area. We, then, give numerical values to SKT's content type, and obtained numerical expression of each human activity

This paper deals with the problem of object tracking and environment mapping inside a space with distributed sensors - Intelligent Space. In a conventional approach the distributed sensors are used for these tasks, however since the sensors are static this has several disadvantages. In this paper in addition to static sensors we introduce the use of a mobile robot as mobile sensor to gather additional information and improve the estimation performance. We discuss the characteristics of such a tracking system, mainly concentrating on a system that uses laser range finders as both mobile and static sensors. Estimation methods based on Kalman Filter and Covariance Intersection are presented and analyzed. Finally, the presented methods are experimentally tested.

In this paper, we analyze and compare the performance of the vertical and the horizontal automated-guided-vehicle transportation systems. We use results in queuing network theory and a transportation simulator to design a hybrid strategy for this study, and to set the appropriate number of agents in the systems. Next, these two transportation systems are evaluated based on cost-effectiveness criteria. For this purpose, the total construction costs of the systems for the various transportation demands are compared. Finally, we provide analytical results to evaluate and to obtain the most efficient system, based on the validity of each system, under different demand scenario. Note to Practitioners-A good design methodology is essential for the study of the optimal layout in an automated container terminal. Port designers need to select the most efficient automated-guided-vehicle (AGV) transportation system, and to set the appropriate number of agents operating in the system. This study presents a hybrid design methodology and a cost-effectiveness comparison of the vertical and the horizontal transportation systems. Our proposed design methodology is able to derive the combinatorial optimal design solutions rapidly, and at the same time pin point the bottleneck in the system. This proposed methodology can be easily applied to any transportation or logistics system, provided the system can be divided into components represented as nodes in a graph. Our results demonstrate that the horizontal AGV transportation system is more effective than the vertical AGV transportation system under most demand scenarios.

This paper proposes the spatial memory as an interface between human and intelligent space (iSpace). The spatial memory regards three-dimensional space as mass storage of computers, i.e. three-dimensional point is treated as an address of stored digital data such as various documents, images and commands for machines. Consequently, we can access stored digital data by indicating a point using our own arms, which we named "human indicator". In this paper, we implement a prototype of the spatial memory system which is supposed to utilize digital data regarded as externalized knowledge. The implemented system is evaluated through two types of experiments. The tendency to forget and the efficiency of task performance are investigated. By applying the t-test under the level of significance 5%, experimental results of the performance efficiency show significant statistical difference between the results with the spatial memory and without it.

The research field on intelligent environments that consist of many distributed sensors and robots has been expanding. Intelligent environments require the functions of extracting and tracking the multiple objects seamlessly to achieve appropriate services to users under the multi-camera environments. Some tracking systems often prepare the color models of the objects in advance. It is difficult to adopt these models to the tracking of the objects that change their color appearance according to the pose. However, model based tracking is efficient for the tracking in the crowded environment. And also, the object color models have to be valid for seamless tracking in the multi-camera environments. We propose the color histogram based object model configuration. This model termed global model is efficient for object tracking and matching. The eigen space of color histograms configured from color appearance in several poses of the object is utilized for the configuration of the global model. Color histogram models needed for tracking of the object that changed their appearance can be rebuilt from the global model. As results of the first experiments, the object correspondence among the different cameras was achieved empirically, and it was described that the proposed object model is effective for the seamless tracking by the distributed cameras

In this paper, we investigate a mobile robot navigation system which can localize the mobile robot correctly and navigate based on observation of human walking in order to operate in the human shared space with minimal disturbance to humans. To realize this system, we utilize many intelligent devices embedded in the environment. The human walking paths are obtained from distributed vision systems and frequently used paths in the environment are extracted. The mobile robot navigation based on observation of human is also performed with the support of the system. The position and orientation of the mobile robot are estimated from wheel encoder and 3D ultrasonic positioning system measurement data using extended Kalman filter. The system navigates the mobile robot along the frequently used paths by tracking control

This article describes a possible application of intelligent space as a platform for fire detection purposes. It enables fast and reliable fire detection, which is important for fire damage minimization. As Intelligent Space is primarily designed for other purposes, such as mobile robot guidance, its application for Are detection related purposes includes only the addition of new software. As almost no new hardware is needed it should be applied in all areas where Intelligent Space is installed.

In this paper, two designs for optimal Automated Guided Vehicle (AGV) transportation systems are presented. One is vertical and the other, horizontal. For these systems, the hybrid design methodology proposed here is used. Therefore, we describe how to model and formulate these transportation systems and derive the design parameters, that is, the optimal design solutions. We next evaluate these two transportation systems based on the various transportation requirements, that is, the demands from a port authority. For this purpose, we compare the systems based on the total costs in constructing them. Finally, the evaluation and analytical results are provided, and the most convenient system is presented based on the validity of each system for the given demand.

Intelligent Space (iSpace) is a space (room, corridor, or street), which has distributed sensory and mobile agents, that is capable to provide intelligent services. In this paper, experimental setup between Hashimoto Lab, University of Tokyo, Japan and Advanced Diagnosis Automation and Control (ADAC) Lab, North Carolina State University, USA is prepared to form an Inter-Continental Intelligent Space. A mobile robot at Hashimoto Lab is controlled by a path-tracking controller at ADAC Lab to track a predefined path with the tracking performance affected by the network time delay. Gain Scheduler Middleware is employed in the control loop to alleviate the effect of time delay. The experimental results of the mobile robot path-tracking has demonstrated the effectiveness of using Gain Scheduler Middleware to compensate the time-delay effect on teleoperation over IP network.

The development of a highly efficient management methodology for an automated container terminal (ACT) poses a problem for port authorities. The focus here is on a transportation system for an automated guided vehicle (AGV) for an ACT. In this paper, we design the detailed management models, i.e., agent cooperation and container storage planning for the transportation system. Then, we optimally design systems that are constructed with the use of the designed management models. Comparisons of the systems are made to evaluate cost effectiveness based on the total construction cost and validity of the management models. Finally, a proposal is made for the most efficient management system.

This paper proposes human-robot cooperative tele-micromanipulation system with novel single-master (PHANToM haptic device) multi-slaves (6 D.O.F parallel manipulator). The different kinematical configuration and the different D.O.F between the master and the slave introduces a mapping problem which can be serious for some cooperative manipulations. The position/force virtual mapping method is implemented in the single-master dual-slave tele-micromanipulation system to realize the human-robot cooperative internal force regulation while grasping task. The generated reference trajectories of both manipulators by the virtual mapping method are shared with the cooperative impedance control of multi-slaves to regulate the internal force while grasping an object. Lastly, an improved internal force regulation using the SMMS (single-master multi-slave) tele-micromanipulation system while grasping an object is verified by the pick-and-place experimental results.

This paper gives contribution to the construction of an image mosaic by pasting together a sequence of photographs taken by a regular digital camera from the same position but in different directions. In order to find the best match between two overlapping images, a fuzzy-genetic based algorithm is presented. A translation vector with a minimal difference between the common picture parts has to be found. The difference is defined using the fuzzyfied contours of each images. The search of the optimal translation is considered as a minimization process. This paper proposes a method that uses genetic algorithms to find the minimum point corresponding to the optimal translation. Using the fuzzy based comparison of the two images yields a fast fitness function, while the implementation of the proposed method in a genetic hardware has a low and variable computational cost. The precision of the method is inverse-proportional with the computational time, which makes it ideal to be used in real time systems.

In this paper, we provide the comparison indicator of the AGV transportation systems. For this purpose, we propose an optimal design methodology for the AGV transportation system by using the queuing network theory. In this methodology, the queuing network theory and a simulation-based optimization method are integrated to obtain the optimal design parameters (i.e., these are the design solutions of this design problem). In this study, two different types of the AGV transportation systems are designed. Then the performance of transportation is compared. Finally, the characteristic of each transportation system that depends on the design parameters is provided.

The possibility of operating in remote environments by means of teleoperated systems has always been considered of relevant interest in robotics. For this reason, in this paper, the relationship between a slave robot and the uncertain remote environment is proposed as the impedance to generate the virtual force to feed back Io the operator. For the control of a teleoperated mobile robot equipped with camera, the teleoperated mobile robot take pictures of remote environment and sends the visual information back to the operator over the Internet. Because of the limitation of communication bandwidth and narrow view-angles of camera, it is not possible to watch the environment clearly, especially shadow and curved areas. To overcome this problem, the virtual force is generated according to both the distance between the obstacle and robot and the approaching velocity of the obstacle. This virtual force is transferred back to the master over the Internet and the master, which can generate force, enables a human operator to estimate the position of obstacle in the remote environment. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. This force reflection improves the performance of a teleoperated mobile robot significantly.

Robots would be able to coexist with humans and support humans effectively in near future. We proposed the intelligent space in order to achieve such human-centered system. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The intelligent space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the intelligent space, a color CCD camera module, which includes processing and networking part, has been chosen. The intelligent space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation, many camera modules are distributed. They cause some errors about object identification among different camera modules. This paper describes appearance based object identification for the distributed vision system in intelligent space to achieve consistent labeling of unknown objects. First, we discuss how to obtain the object color information for constructing the color appearance based model. Then, we propose the global color model based on the color information for the object identification.

The Intelligent Space is a space where we can easily interact with computers and robots, and get useful service from them. To achieve such a space, a distributed intelligent networked device (DIND) has been proposed. Many DINDs are installed in a space and they cooperate each other to make the space to become an Intelligent Space. In this paper, an optimal DIND placement, self-calibration of DIND and handover protocol for cooperation among DINDs, are described.

In this paper, the Intelligent Space concept is applied for helping disabled or blind persons in crowded environments such as train stations, or airports. The main contribution of this paper is a general mathematical (fuzzy-neuro) description of obstacle avoidance method (walking habit) of moving objects (human beings) in a limited area scanned by the Intelligent Space. A mobile robot with extended functions is introduced as a mobile haptic interface, which is assisted by the Intelligent Space. The mobile haptic interface can guide and protect a blind person in a crowded environment with the help of the Intelligent Space. The Intelligent Space learns the obstacle avoidance method (walking habit) of dynamic objects (human beings) by tracing their movements and helps to the blind person to avoid the collision. The prototype of the mobile haptic interface and simulations of some basic types of obstacle avoidance method (walking habit) are presented.

In this paper, control schemes for the master haptic interface are mainly discussed. We proposed the tele-micromanipulation systems, which enables human operators to operate micro-tasks, such as assembly or manufacturing, without feeling the stress. The paper focuses on the haptic interface, which gives the operators the feeling of presence. The mechanism applied in the human interface device often has a reasonable immanent friction. This friction must be compensated in a way that the operator cannot feel this friction force, but only the force from the manipulated environment. The main contribution of this paper is a direct model based chattering free sliding mode friction estimator and a compensator for the human interface device. The experimental results obtained are presented.

Intelligent space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. It is desirable for a mobile robot to carry out human-affinitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow walking human as stably and precisely as possible.

In this paper, control schemes for haptic interface for micromanipulation systems is mainly discussed. We have proposed a tele-micromanipulation system, which enables human operators to operate micro tasks, such as assembly or manufacturing, without feeling stress. This paper focuses on the haptic sense, which gives the operators the feeling of presence. The mechanical instrument applied in the human interface device usually has a reasonable immanent friction. This friction must be compensated in a way that the operator should not feel this friction force but the force from the manipulated environment. The main contribution of this paper is a direct model based chattering free sliding mode friction estimator and compensator for a mechanical instrument. Experimental results are presented.

The intelligent space is a space where we can easily interact with computers and robots, and get useful service from them. In such a space, location information is very important, since the agents cannot provide proper service to a proper people at a proper location without location information. Our positioning system uses CCD cameras. It is important to determine where to put the cameras for the best localization depending on the tasks in the space. The main purpose of this paper is to consider how to arrange cameras for the best localization in the intelligent space.

Intelligent Space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. It is desirable for a mobile robot to carry out human-affinitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow a walking human as stably and precisely as possible.

A human-machine interface is proposed for teleoperated nano scale object interaction and manipulation. Design specifications for a bilateral scaled teleoperation system with slave and master robots, sensors, actuators, and control are discussed. Phantom and home-made haptic devices are utilized as the master manipulator, and a piezoresistive MEMS fabricated probe is selected as the slave manipulator, and topology and force sensor. A force reflecting servo type teleoperation control is chosen, and initial experiments are realized for interacting with silicon surfaces and nano structures. It is shown that fine structures can be felt on the operator's finger successfully.

A dexterous tele-micromanipulation system using haptic interfaces has been developed for the application in assembling electrical/optical parts for electrical devices, micro-machine, etc. The paper describes the development of visual operation support systems for tele-micromanipulation systems. Because of its better manipulation positioning accuracy, stiffness and speed characteristics, a parallel mechanism micromanipulator was chosen for our system. While the parallel manipulator has the above-mentioned merit, there is the disadvantage that the parallel mechanism's workspace is narrow and the translation motion workspace changes depends on the posture of end-effector. Providing workspace information in real time to the human operator, he can recognize the workspace and helps planning the micromanipulation process. A parallel manipulator motion is restricted by three factors: mechanical limits of the passive joints, collision between the links and actuators limitations. Results of numerical workspace analysis considering the above factors are shown. Based on the workspace analysis, a VR simulator and workspace display systems for micromanipulator are proposed. The feasibility of the use of a workspace display system for micromanipulation is then discussed.

We propose a method of guiding mobile robots in a networked space. To watch human and robots, distributed sensor devices with processors are located around the networked space. In this space, robots as well as the human are supported informatively and physically. The distributed sensor devices guide mobile robots in this space and navigation with high adaptability is realized. The simulation and experimental results including the camera arrangement and robot guidance with distributed sensor devices are shown.

The development of techniques for autonomous mobile robot navigation has been in focus for several decades . The main objectives of this paper are twofold. One is to extend the potential based guiding (PBG) model to a more general form that can be approximated by a common type neuro-fuzzy algorithm. The extended model eliminates the strongly alternating behavior of PBG. The second is to propose a computation complexity reduction method for the general form of the neuro-fuzzy technique. Same examples are given to show the effectiveness of the extended guiding model.

In this paper, we discuss about micro teleoperation with haptic interfaces. We developed the micro teleoperation systems for micro tasks, such as assembly or manufacturing. We show about structure of master/slave manipulators, its control and experimental results of teleoperation with the manipulators in this paper. We introduce the haptic interface that provides operators the sense as if he/she touches the expanded micro objects with his/her fingers. This micro tele-manipulation system is a new tool, which enables human operators to touch and feel the expanded micro objects with their fingers.

This paper describes our concept on the intelligent space. The intelligent spaces are rooms or areas that are equipped with sensors, which enable the spaces to perceive and understand what is happening in them. By using such features, people or systems in the intelligent space are supported and can use additional functions. The intelligent spaces are expected to have a broad range of applications such as in homes, offices, factories etc. The basic components, which compose our experimental system, are shown in this paper with descriptions.

In this paper, a fine particle positioning system using a piezoresistive cantilever, which is normally utilized in atomic force microscopy, as the manipulator is proposed. Modeling and control of the interaction forces among the manipulator, particle and surface have been realized for moving particles with sizes less than 3 /spl mu/m on a Si substrate in 2D. Optical microscope (OM) is utilized as the vision sensor, and the cantilever behaves also as a force sensor which enables contact detection and surface alignment sensing. A 2D OM real-time image feedback constitutes the main user interface, where the operator uses mouse cursor and keyboard for defining the task for the cantilever motion controller. Particle manipulation experiments are realized for 2.02 /spl mu/m goal-coated latex particles, and it is shown that the system can be utilized in 2D micro-particle assembling.

Usually localization in mobile robots is interested in only the geographical position of the robot in space. However, to utilize mobile robots in general environments such as a hospital, an office, a school etc., we need more than conventional localization. We propose a new localization method that watches the entire space as well as the mobile robot. Some experimental results are shown to show the performance and the merits of proposed localization method.

In this paper, a teleoperated micro/nano scale touching system is proposed, and micro/nano contact mechanics models are introduced. Using a 1-DOF haptic device, force-reflecting servo type scaled teleoperation controller, and atomic force microscopy cantilever tip, touching experiments and virtual reality simulator for micro/nano-touch are realized. Scaling issue of the micro/nano forces and positions is discussed and possible solutions are proposed. For the first time upon our knowledge, such issue is discussed with nano scale experimental results. Experimental results show that micro/nano contact force feedback can be held for flat surfaces with the proposed system.

A new concept for constructing an intelligent mobile system is proposed. We describe reasons for the necessity of a new architecture for mobile systems in intelligent spaces. The intelligent spaces are room or area that are equipped with sensors, network and computers. The intelligent spaces are expected to be authentic future environment. If environment gets intelligence, it is not a distinct part of an intelligent mobile system any more and also the mobile system becomes a physical agent of the intelligent space. In this paper, we do some experiments to show what are possible for a mobile robot in an intelligent space.

Describes the intelligent manufacturing system (IMS) program progress in the autonomous assembly robot cell research. We focus on the information which is generated by the designers during the product development process. From the assembly process viewpoint, this information is extracted and integrated into the product model as an assembly model. This information is called assembly model data (AMD). Therefore, the main purpose of our research is to investigate the utility of AMD and the best format for these data in the assembly process. To solve the assembly problem, a 3D CAD data driven assembly robot cell (ARC) system was proposed. Robot task programs for the assembly process are generated automatically from 3D CAD data and AMD with this system in the virtual environment. The system can show the designers visually the difficult parts of an assembly. ARC with only products' CAD data and AMD can then assemble actual products in the real environment using a hand eye system equipped with a laser range finder. The products' CAD data and AMD are supplied to each ARC through a network. The data format was evaluated through loading actual AMD in the ARC system.

This paper presents a new type of human interface with force feedback attached to an arm, which we named Sensor Arm. The Sensor Arm can be utilized as an interface for interactive communication with the virtual environment and as a master manipulator of a tele-operation system. The number of degrees-of-freedom (DOF) of the Sensor Arm is seven, which is the same DOF of a human arm. Angle and torque of each joint can be measured. Moreover, in this system, force feedback can be realized at each joint of the human arm. To measure human force a new type of force sensor system is proposed in the Sensor Arm system. The structure of the Sensor Arm system and the experimental results are shown.

A tele-nanorobotics system using an atomic force microscope (AFM) as the nanorobot has been proposed. Modeling and control of the AFM cantilever, and modeling of nanometer scale forces have been realized for telemanipulation applications. Besides 3-D virtual reality visual feedback in the user interface, a 1 DOF haptic device has been constructed for nano scale haptic sensing. For feeling the nano forces, a bilateral teleoperation control system with virtual impedance approach has been introduced. Initial experiments and simulations on the AFM and teleoperation system show that the system can be utilized for different tele-nanomanipulation applications such as 2-D nano particle assembly or biological object manipulation.

In this paper we present a system that is able to give force feedback for the handling of virtual objects to a human operator and discuss how this system can learn low-level reflective behaviors from the human. A dynamic force simulator (DFS) that simulates object dynamics, contact model and friction characteristics of the human hand was developed to interact with the object in virtual reality. The DFS allows calculation and feedback of appropriate forces to the force controlled actuators of a glove type haptic interface. The measured data is used for task-teaching of the robot in the remote site. However usually the task can not be achieved by simple playback teaching. As each task execution is different due to various sources of small errors a low-level motion behavior to compensate for this errors is needed. In this paper, this function is assumed to be a reflective behavior and we acquire it by learning from human. Two learning schemes, neural nets and radial basis functions are experimentally evaluated.

Intelligent spaces are rooms or areas that are equipped with sensors such as microphones or cameras that enable them to perceive what is happening in them. In such spaces that have an intelligence of their own a world model no longer is something the robot has alone but a service offered by the information infrastructure of the space. In this article we show how such an intelligent space can generate a topological map for robots by looking at the movements of people in the room. We describe the stereo vision system that is capable of tracking the 3D movements of several humans in real time and give experimental results obtained in a real-world environment with several people.

Real-time obstacle avoidance is essential for the safe operation of mobile robots in a dynamically changing environment. This paper investigates how an mobile robot can respond to unexpected obstacles while following a path planned by a global path planner. The obstacle avoidance problem is formulated using a decision theory to determine an optimal response based on inaccurate sensor data. It is shown that our proposed method avoids properly obstacles through simulation results.

In this paper we present a dynamic force simulator (DFS) for force feedback in human-machine systems. DFS simulates object dynamics, contact model and friction characteristics of the human hand interacting with the object in virtual reality. Interaction with DFS allows calculation and feedback of appropriate forces to the force controlled actuators of the sensor glove we have developed. In the future we will use this system to analyze human dextrous manipulations called human skill.

A key goal in dextrous robotic hand grasping is to balance external forces and at the same time achieve grasp stability and minimum grasping energy by choosing an appropriate set of internal grasping forces. Since it appears that there is no direct algebraic optimization approach, a recursive optimization, which is adaptive for application in a dynamic environment, is required. One key observation in this paper is that friction force limit constraints and force balancing constraints are equivalent to the positive definiteness of a certain matrix subject to linear constraints. Based on this observation, we formulate the task of grasping force optimization as an optimization problem on the smooth manifold of linearly constrained positive definite matrices for which there are known globally exponentially convergent solutions via gradient flows. There are a number of versions depending on the Riemannian metric chosen, each with its advantages, Schemes involving second derivative information for quadratic convergence are also studied. Several forms of constrained gradient flows are developed for point contact and soft-finger contact friction models. The physical meaning of the cost index used for the gradient flows is discussed in the context of grasping force optimization. A discretized version for real-time applicability is presented. Numerical examples demonstrate the simplicity, the good numerical properties, and optimality of the approach.

In this paper we describe the 4-fingered dextrous robotic hand with 24 degrees-of-freedom (DOF) we have developed. At each finger-tip a 6 DOF force/torque sensor is attached to measure contact forces directly. A heterogeneous parallel computing architecture based on transputers is used to implement the proposed grasp controller and the underlying hybrid position/force controllers for each finger. Experimental results of object trajectory following, object stiffness and friction coefficient estimation are shown.

For dextrous robotic hand grasping a key goal is to balance external and internal grasping forces to assure a stable grasp and low grasping energy. In this paper, the authors view the task of grasping force optimization as a linearly constrained semidefinite programming problem for which there are known globally exponentially convergent solutions via gradient flows. A key observation is that the nonlinear friction constraint at each contact point is equivalent to the positive definiteness of a suitable matrix containing the contact wrench intensities. A recursive version is presented, and numerical examples demonstrate the simplicity, the good numerical properties, and optimality of the approach.

The artificial potential field method is frequently employed for obstacle avoidance both of mobile robots and of manipulator arms. This paper extends previous results for planar problems to the general n-dimensional case. The complexity is reduced by projecting the n-dimensional workspace onto a 2D subspace called operation plane. Furthermore, only the closest obstacles are taken into account when designing the artificial potential field. Still, global convergence is achieved. The methodology is illustrated with several numerical examples.

A key problem in robotics is the estimation of the location and orientation of objects from surface measurement data. This is termed pose estimation. A fundamental task is the pose estimation of known quadratic surfaces from, possibly noisy, data. A solution for this task facilitates pose estimation for more complex objects. Current algorithms frequently converge to local minima of the performance index and/or pay a high computing cost and/or are sensitive to noise, that are unsuited for online applications because of the intensive computer effort required. The goal is to develop a fast and robust algorithm for pose estimation using range data. Here, pose estimation is carried out using algebraic techniques in a two stage optimization procedure involving least squares estimation, or better the method of instrumental variables, and 3/spl times/3 matrix diagonalizations. The procedure leads to zero pose estimation error in the noise free finite data case, and in the case of infinite data with additive white noise.

Proposes a position estimation method and a path generation between current position and goal point for mobile robots. Dead reckoning has been commonly used for position estimation. However this method has inherent problems because it also accumulates estimation errors. In this paper, the authors propose a new method to increase the accuracy of estimated positions using a matching method which is applied with a least squared scheme. This approach uses features, such as corner points and edges of the object in the task environment instead of land-marks. Also, the authors discuss how to establish an environment database and propose a genetic algorithm in order to find an optimal path. It is shown that: it is possible to estimate the position of mobile robot precisely, errors are not cumulated, and the path generation method is very fast.

This paper proposes the idea of a manipulation skill mapping for dexterous manipulation task modeling. Mapping between desired object task trajectories and finger contact point locations, this skill mapping can efficiently describe complex manipulation tasks, where contact states of the fingers change during the task. Further issues on how this skill mapping can be acquired and transferred for execution by dexterous robotic hands, are discussed. Examples show the applicability of the proposed scheme.>

Intelligent cooperative manipulation is proposed as a new paradigm for human-machine interaction and cooperation. Aiming at intelligent assistance of human operators the information and power flow between operator-system-task environment is carefully analyzed using a virtual reality to simulate the task environment. Central issue of this virtual reality is the dynamic force simulator (DFS) for feedback force calculation proposed in this paper. The DFS simulates object dynamics, contact model and friction characteristics of the human hand interacting with objects in the virtual reality. An example shows the efficiency of the proposed realization scheme of the DFS.>

This paper proposes a manipulation skill mapping for dextrous manipulation task modeling in the intelligent cooperative manipulation system-ICMS. Mapping between desired object task trajectories and finger contact point locations, this skill mapping can efficiently describe complex manipulation tasks, where contact states of the fingers change during the task. Further issues discussed are how this skill mapping can be acquired into the manipulation skill database of the ICMS and transferred for execution by dextrous robotic hands. Examples show the applicability of the proposed scheme.>

We developed a dextrous robotic hand system with four identically structured fingers. Each finger has 6DOF (degrees-of-freedom), so the hand has a total of 24DOF. Further we developed a 6-axis force and torque sensor to detect forces and moments at the finger-tip, so it is possible for this robotic hand to control grasping forces during object manipulation. In this paper we show some experiments of grasping and manipulating objects using a 6-axis hybrid controller approach. Using data from the force-torque sensor and appropriate position and force references in control, object parameters like friction and stiffness can be estimated.>

This paper discusses information and power flow in the Intelligent Assisting System (IAS). The IAS includes an intelligent manipulation assistant to a human operator, where information as well as forces between the operator, the IAS and the task environment are exchanged. A manipulation skill database enables the IAS to perform complex manipulations on the motion control level and intelligently assist the operator. As a first approach to the IAS the authors have been developing a skill acquisition and transfer system using a sensor glove for force feedback to the human operator. The dynamic behavior of the grip transformation matrix is regarded as the essence of the performed manipulation skill shown with a simple manipulation example. A detailed analysis of force transformations between hand and object space yields a method for acquisition of the grip transform dynamic behavior accumulated in the skill database. Further this paper defines a control algorithm realizing object task trajectories and its feasibility is shown by simulation.

The approach presented is this paper is based on two ideas: (1) on the planning level an electrostatic potential field in the configuration space of the robot is used. The generalized force curves are attractive to the goal point avoiding obstacles without local minima; (2) on the control level the system follows these force curves using sliding mode control. The system is attracted to the swiching manifold using sliding mode and therewith the systkm is robust to disturbances and parameter variations. the system control variables so that sliding mode occurs in the vicinity of the force field curves and the system is attracted to them. This means that the system trajectories are identical to the force field curves. Sliding mode assures robust control performance despite unknown disturbances and parameter variations.

The approach described consists in constructing potential fields in configuration space like an electrostatic one with changes distributed in such a way that the generalized force curves are attracted to the goal point and avoid obstacles. The system follows such force curves by using sliding mode. The strategy of robot path obstacle avoidance control with sliding mode is presented and discussed in the two-dimensional space.>

VSS controller is suited for robotic arms where the robust performances in the presence of parametric variations and disturbances are most important. The practical design of such robust VSS controller is discussed in this paper. The significant issue in the design of VSS is to avoid the chattering caused by the switched input. This problem is solved by introducing the continuous control input instead of switched input. The practical design of such control is obtained by using "Balance Condition". The "Balance Condition" is derived from the careful consideration on the bandwidth of plant dynamics and VSS controller, and gives many benefits in applications of VSS controller to actual systems. This paper shows the validity of balance condition in the robotic arm control. Simulations and experimental results using a position servo system (one degree of freedom robotic arm) are discussed from the practical point of view of robust control. In order to investigate multi-joint cases, simulations with a two-linkage robot arm are provided.

The high-gain effect of sliding mode control based on VSS (Variable Structure System) suppresses the uncertainties due to parametric variations, external disturbances and variable payloads. The resulting system is completely robust whereas the obtained control law is simple and easy to be applied to on-line computer control. In this paper, the sliding mode controller for MIMO (Multi-Input Multi-Output) robot arm is realized using "Estimated Inertia Matrix" which has inevitably small uncertainties dependent on arm structure and inaccuracies of computation. This technique contributes to practical design of sliding mode for MIMO system compared with the well-known "Hierarchy Method". In addition, simple nonlinear compensation and proper continuous function (instead of relay type component) with "Integral Mode" are implemented to diminish chattering caused by switching input. The validity of this control is confirmed in simulations and experiments where the system shows the robust performances in spite of the existing nonlinear interactions and unknown parametric changes.