We propose a new motion planning method of a 7-DOF redundant manipulator. In this method, motion planning for obstacle avoidance is executed with the configuration space considering the actual range of joint motion. In addition, the manipulability and avoidance manipulability of the redundant manipulator are considered in the proposed motion method.

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When simulating and controlling robot dynamics, it is necessary to know the inertial parameters and the joint dynamics accurately. As these parameters are usually not provided by manufacturers, identification is then an essential step in robotics. We propose a method to estimate closed loop structure robots inertial parameters without torque sensor, using generalized coordinates of base-link, joint angles and external forces information. However to use this method it is mandatory to prove that the base parameters identifiable arc the same as with classic torque-based methods. This paper presents a symbolic preliminary proof using examples, and inertial parameters of closed loop structure formed by two manipulator robots arc identified from the method based on the use of dynamics of the base-link. And it is aimed for verification of the identifiability of this method.

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In this paper, we have investigated for factors of speeding-up of sensor based motion planning for 3-DOF manipulator. An autonomous robot requires a function for moving based on sensor information without collision with an obstacle. We searched for factors of time to generate a path of CPFS (Closest Point First Search) algorithm based on the Bug2 algorithm proposed by Lumelsky and extended Bug2 algorithm. We tested using the 3-DOF manipulator covered proximity sensor with these methods for verification. Using computer simulation, we experimented in the same environment and compared with the experimental result. As a result, reducing searched configuration is important to generate a path quickly.

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RoboCup Soccer Simulation League 2D is a game competition where independently moving software players (agents) play soccer on a virtual field inside a computer. This league is used as a testbed in research on multiagent systems. This paper deals with a policy of an agent when he holds a ball. In Agent2D, the policy uses a game tree whose nodes are predicted states caused by agents' actions and a positional evaluation function that evaluates the predicted states. We designed this positional evaluation using heuristics on soccer and applied the policy gradient reinforcement learning algorithm to learning weight parameters included in the evaluation function.

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This paper introduces the design considerations of an outdoor use autonomous mobile robot that travels in an athlete track at a speed of about 20 km/h. This robot is intended to use for the pace making training of long distance runners. First, based on the interview on pace running method to long-distance runner, we discussed design considerations for such robot, and decided its working environment to 400m track field. Also, we designed remote monitoring function that presents runners' condition in real time to the remote coaches. Next, we explained the prototype of mobile mechanism, and its evaluation result through experiments. Last, we described future plan of the development.

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This paper describes the robot contest produce competition and its purpose on creativity education. In this competition, participants plan an original robot contest for children including the rule book, the field, the robots for demonstration and the promotion video. Then, they present the robot contest as the trial management. This competition aims to promote their creativity, especially the problem-raising ability and the problem segmentation ability, and presentation ability too. The robot contest produce competition 2013 is also reported as an embodiment.

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We are studying walking control of a humanoid robot in consideration of motor temperatures. In the RoboCup, it is serious problem that humanoid robot can not walk fast and stable for 20 minutes. Because the autonomous robot with control circuit is relatively heavy, the servo motors may tend to get overheat and shutdown to prevent damage. The objective of this study is to maximize the walking speed while keeping the temperatures of the servomotors below the maximum permissible one. The robot estimates the motor temperatures, and then it modifies the walking pattern. In this paper, we investigate the relationship between the power consumption of the motor and the walking pattern by simulation. And, we verify its validity using the real robot.

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We developed the control system for RoboCup soccer robot with MATLAB / Simulink. Action and strategy of the robots is sophisticated in RoboCup soccer middle sized league. Concerted action by multiple robots depends on the circumstances of the operation. Behavioral algorithm that can handle dynamic changing environments is necessary. We aim to realize the ball passing behavior in concerted action.

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We are studying on the influence of the state transition of touch ground on the biped robot walking. We have been developed a small humanoid robot "Accelite" for the RoboCup. It can walk stable and fast relatively. However, in the RoboCup2010 Singapore, the robot can not walk stably because the field is slippery. Then, we found the robot can walk stably if the sole angle is changed in trial and error. In the previous study, we analyze the influence of the sole angle and discuss why the angle is important for the stable walking. In this paper, we measure the transition of touch ground and the trajectory of the center of gravity. Then, we analyze the behavior of the walking.

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Japan is a developed country of the robot, and study of various robots have been actively conducted. However, most robots have been put to practical use in society is an industrial robot. Agricultural robots are not practically used yet. Being able to introduce agricultural robot disseminate, it can be expected labor saving, automation, and productivity improvement. We aim at the development of agricultural robot through the holding of competitions of the tomato harvest. It unites the interest of robot technology and interest in the natural environment. It is an object of the invention is introduced into agricultural technologies developed in the course of the competition, and disseminating agricultural robot.

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This paper describes the hardware and software of bipedal robot leg architecture for RoboCup Humanoid League such as the RoboCup teen size team FUB-KIT. Team FUB-KIT was founded in 2012 on a collaboration between Free University of Berlin and Kyushu Institute of Technology. The research is aimed at developing bio-inspired legged mechanisms and controls. Both research groups have been working in Robotics research as well as in RoboCup. We organized the joint RoboCup team and won the third place at RoboCup 2013 Eindhoven Humanoid Teen Size League. The developed biped robot is introduced in this paper.

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RoboCup is an international join project to promote Artificial Intelligent (AI), robotics, and related field. It is an attempt to foster AI and Intelligent robotics research by providing standard problems where a wide variety of technologies can be integrated and examined. In RoboCup, soccer game is selected as a main topic of research, aiming at innovations to be applied for socially significant problems and industries in the future. We also have organized RoboCup team "Hibikino-Musashi" Middle-Size League soccer competition. In this paper, we introduce the next generation soccer robot platform "Musashi150" with ball keeping ability and fast movement.

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This paper presents very simple descriptor for local image feature that is detected by DOB (Difference of Boxes) proposed in CenSurE. Image feature is often used to navigate a mobile robot, and some methods that are robust for scale and illumination change are developed such as SIFT and CenSurE. However these descriptors still has heavy computation, and to use them is a big burden for some low spec computers. Therefore we proposed a simple feature descriptor that is strong for scale and illumination change based on census transform. As experimental results, the proposal method has ability of matching accuracy that is almost same as SIFT for scale change and is better than SIFT for illumination change.

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We are developing a semi-autonomous robot system for power distribution line maintenance works. The robot system autonomously performs primary tasks, for example "Insert the bolt" to reduce the load on operators. To perform the tasks autonomously, the robot system has to construct database of work environment which is a set of positions and orientations of the objects in work environments around electric poles. So we applied ICP (Iterative Closest Points) algorithm to the point cloud measured by LRF(Laser Range Finder) to estimate the positions and orientations of the objects. Also, we are using the Kd-tree in order to perform at a high speed processing.

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Autonomous robots that replace humans are currently in high demand in the manufacturing sector worldwide. However, these robots cannot be used in unknown environments because most of them are controlled by sequence controls. To solve this problem, cameras are needed as vision sensors that can recognize the outside environment. It would enable industrial robots to more effectively perform the handling tasks by combining the image recognition technique with the feedback and sequence control techniques. In this search, we aim at improving the camera calibration accuracies in order to accurately calculate the shape and position of an object from the image information obtained by two cameras. Then, we focus on the positions of two cameras. We have proposed the positions of two cameras in the past to improve these calibration accuracies. However, we require wide floor ranges for the two cameras in the past reserch. By reducing the floor area of an industrial robot, it is expected to improve productively and investment costs. Therefore, improvement of the position of cameras of the past study is needed. So, in this reserch, we newly propose the positions of two cameras in a small area by taking into consideration calibration accuracies. First of all, we examine the influences of the positions of two cameras for calibration accuracies. Next, we determine the optimal camera position from a simulation based on the modeling image noise obtained through experimentation. After that, we verify the effectiveness of the positions of two cameras by sorting operation accompanied by identification task and robotic grasping task.

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We are developing a semi-autonomous robot system for power distribution line maintenance works. The robot system autonomously performs primary tasks, for example "Insert the bolt" to reduce the load on operators. The system is multi agent system which constructs 6 agents and 2 databases. The robot executes to read a work sequence is written by task level. Approach method is to measure 3 dimension position of work object by a camera. This time, we have detected the edge of a line segment from the image captured bolts on a cross arm using flash. We estimated the position and posture by matching the edges of the model it.

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Surgical task automation is expected to improve the performance of robotic surgery. Although segmentation of surgical threads in laparoscopic images is one of prerequisites for surgical task automation, the surgical thread segmentation in an unstructured environment is a very challenging problem. This study aims to develop a scheme for surgical thread segmentation for surgical task automation. We propose a segmentation algorithm wherein the continuity of a thread is utilized using the Kalman filter. Once a user clicks one point of the surgical thread in the image, the system traces the thread from the clicked point and segments the rest of the thread automatically. The algorithm was tested using the images of the thread in both structured and unstructured environments.

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In support of daily life by a robot, the autonomous mobile robot to recognize the behavior of the person and track the human is important. In this paper, we newly proposed automatic detect human tracking measurement using RGB-D camera. First, the clothes information and the body information are learned. The range which searches is limited using Kalman Filter that human detection. By adding gesture recognition, human and a robot enabled it to communicate. Experimental results in indoor environment have shown the effectiveness of the proposed method.

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The demand that a robot manipulates deformable objects. It is important for a robot to recognize these forms by using image information. Form estimation algorithm of deformable object based on image information is proposed in previous research. In this algorithm, first, paired images are captured by CCD camera with rotating around a target object. Secondly, corresponding points are obtained between paired images by application of optical flow. Finally whole scries of points of a target object in three dimension are reconstructed based on stereoscopic vision. It is important to discriminate whether the captured object is planar object or linear object from points group, so that a robot can calculate a manipulation planning of the object. In this research, algorithm to distinguish between a planar deformable object and a linear one from projection image on vertical section of points group is proposed.

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In previous, we proposed a general object recognition method to use the general shape concept of object, an example of which for a chair is "it has a seating surface at certain height", "it may have a back surface", etc. This method doesn't need learning some features of object. However, there is a problem that recognition is not possible if the seat and back are apart in such a case of pipe chair. To address this problem, we propose a method to use the general concepts based on not only object shape but also co-occurrence, such as "desk and chair exist in the neighborhood of each other". The effectiveness of proposed method was experimentally verified in practical several situations.

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We proposed the object detection method based on saliency map by using reference image containing complex background for service robot. In the previous detection method, images which the user prepares in advance contain mostly simple background. However, in order to make robots do the daily tasks, it is desirable for these robots to be able to detect an object by using snapshots which contain a complex background. In order to decrease effects of features in the background, our proposed method classify local features based on saliency from images. This paper shows the efficacy of proposed method and that our service robot detects some object according to the proposed method.

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Our paper newly presents unsupervised feature representation method for images called informative census transform (ICT) based on statistical analysis of CT binary features and submodular optimization. A new cost function is designed to measure the informativeness of each binary feature by considering (1) an individual informativeness of features and (2) relative informativeness between binary features. Moreover, two constraints are designed by considering sub-modular characteristics to guarantee theoretical performance and fast optimization via simple greedy algorithm. Experimental results show that the proposed ICT features with two constraints outperforms the traditional CT features in terms of recognition performance and computational cost.

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In this paper, we propose a method to estimate position and orientation of objects for ring-type caging by visual sensor. Caging is a method to make an object inescapable from a region closed by rigid bodies such as a position-controlled robot hand. Ring-type caging is a type of caging in which a robot hand capture an object with holes, such as mugs, by grasping its handle part. Ring-type caging can be achieved by robots autonomously if the position and orientation of object, particularly that of its hole part, is retrieved. We show some experimental results that position and orientation of scissors are estimated.

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This paper describes a 3D plane detection method of an intelligent robot to achieve a task grasping an unknown object based on the information of a 3D range sensor. The previous methods of plane detection have problems which are the high computational cost and the low-accuracy of small object detection. To solve the problems, we have proposed a retinal structure-based plane detection method. The proposed method consists of a simple plane detection using region growing, a visual attention model based on the retinal structure and the integration of detected planes. To verify the proposed method, we show that the computational cost of the method is less than that of the previous methods through several experiments.

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We developed an algorithm and architecture for calculating the optimal binocular disparity efficiently based on the binocular disparity energy model with a coarse-to-fine strategy. Because the model requires a lot of spatial filtering whose computational cost is very high, we designed hardware architecture so that it executes the required spatial computation in real time by using a resistive network and a field programmable gate array (FPGA). The resistive network enables fast multiple band pass filtering required for implementing the disparity model. The algorithm takes advantages of the hardware architecture to calculate the optimal disparity from multiple band-passed images. The optimal disparities calculated from band-passed images with a low and high frequency offer a wide detectable disparity range and high precision, respectively. We evaluated the algorithm by using a software simulation. The results showed that the algorithm offers both a wide disparity range and high precision.

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Autonomous mobile robot for indoor aiming at alternative of human labor work has been studied by various researchers. However, since most of them are performing floor movement for transportation, they must inevitably consider disturbances on the floor, such as unpredictable obstacles and walking people. Therefore, their control must become complicated and such robot must carefully move at low speed. To solve such issues, here, we employ flight robot as a mobile robot, which can move in the air where disturbance is clearly less. Furthermore, we employ line-tracking methodology for automatic moving control, because its infrastructure installation is very simple, economical and feasible for various situations. This paper reports an automatic control method for flight robot by line-tracking with optical camera and its experimental results.

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A method for generic object recognition to categorize such as desk, chair, etc., has been already proposed by authors, in which point cloud data captured by a range image sensor (Kinect, Microsoft) is used. The point data is segmented to several regions based on depth data. As for each segmented region, the point distribution data and the region size data of width, depth, and height are considered. The data is input to AdaBoost classifier. The classifier judges whether the region is object or not. However, two (or more) objects close to each other are likely segmented to one overlapping region. To address this problem, a new segmentation/recognition method is proposed in this article as follows: i) an overlapping region is divided to several small regions based on RGB data using k-means method, ii) all combinations of small regions are considered. Depth data of all combined region is input to AdaBoost classifier, and iii) combination of which AdaBoost output is the highest is adopted as the segmentation/recognition result. This method imitates a human who seems to repeat segmentation and recognition complementally. As for overlapping chair and desk, segmentation and recognition were successfully conducted by proposed method.

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The ambient light is changed by a factor of nature such as a weather, season and time, and also changed by a factor of neighboring apparatuses such as an arc light of the welding apparatus. The glossy object reflects an ambient light and cause blown out highlights. Size and the position of the blown out highlights are changed by the change of the ambient light. These make image processing difficult. Known colored light was used to solve this problem. In this paper, the detection system of the glossy sealing component is explained.

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This paper presents a new object classification method using range and reflectance data obtained by a laser scanner. Several laser scanners produce not only range data but also reflectance which shows the power of reflected laser as a side product of range data. The proposed method utilizes both information for object classification. Since laser reflectance contains appearance information, the proposed method classifies objects based on their shapes and appearances from range and reflectance data. Moreover, we extend the conventional Histogram of Oriented Gradients (HOG) so that it couples geometrical and appearance information more tightly. We show the validity of the proposed method through experiments in real scene.

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A compact ego-motion estimation system is required for autonomous control of an unmanned air vehicle whose demand is increasing recently. In this study, we proposed an algorithm that estimates the ego-motion by discriminating optical flow patterns, inspired by insect's visiomotor control system. First, this algorithm calculates the local velocity from images of the surface of the ground by using a motion-detection model inspired by an insect's visual system. Then, the algorithm integrates the local velocity to estimate ego-motion. We tested this algorithm assuming that the vehicle moves horizontally, rotates in yaw and changes its altitude.

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A novel simultaneous intermittent tracking method is proposed for motion-blur-free and high-brightness video recording of fast-moving objects. To observe fast-moving objects in microscopic view, we developed a prototype motion-blur-free video recording system, which consists of a real-time high-speed vision system and a high-speed piezo actuator. Several experimental results demonstrate the effectiveness of our tracking method for motion-blur-frce video recording without decreasing the exposure time of the vision system.

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In recent years, image retrieval has become an important building block for various robot vision systems. Applications include object recognition and place recognition. In those approaches, a set of local feature descriptors such as SIFT (Scale Invariant Feature Transform) are extracted from the visual images and used for indexing and retrieving the view images. A difficulty arises in dealing with a large size image set because the time and spatial cost required increase in proportion to the number of local features per image. To address the scalability issue, we propose a novel database augmentation technique. In it, useless features that have low discriminativity and repeatability arc detected in images and eliminated to reduce time and spatial cost. The proposed database augmentation technique is verified in image retrieval experiments.

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We consider the task of long-term visual SLAM, i.e., simultaneous localization and mapping, in a partially changing environment (SLAM-PCE). The main problem we face is how to obtain discriminative and compact visual landmarks, which are necessary to cope with changes in appearance in an environment and with a large amount of visual information. We address this issue by proposing the use of common object patterns, which are inherent in typical environments (e.g., indoor, street, forests, suburban, etc.), as visual landmarks for a SLAM-PCE task. In our contributions, we describe our approach, "part-based SLAM", and validate its effectiveness within a standard problem of view image retrieval. The main novelty of this approach lies in that the common landmark objects are extracted in an unsupervised manner via common pattern discovery, and can be used for compact characterization and efficient retrieval of view images. Our method is also innovative in its use of traditional bounding box-based part annotation: an image is represented in a compact form, "bag-of-bounding-boxes (BoBB)"; and then, the scene matching can be solved efficiently as a low dimensional problem of matching bounding boxes. The results of challenging experiments show that it is possible to have high retrieval performance with compact image representation with only 16 words per image.

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We proposes an image processing algorithm for texture edge detection. In the proposed method, multiple template images are obtained from each texture area which consists of periodic pattern, and are used for segregating the texture in the image. This algorithm detect not only texture edge but also defects in the target image. We examined the performance of the algorithm in an image inspection of mask patterns used for manufacturing industrial products.

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This paper describes a method of obstacle detection in the fish-eye camera image for GPS-Non-Line-Of-Sight(NLOS) satellites detection. Recently the development of the autonomous mobile system(AMS) is more expected for example an auto-pilot car. A GPS measurement is widely used for estimating self-position for such AMS. It can measure the position without premeasured emvironmental data like a map-matching. However, in the urban canyon, GPS measurement accuracy deteriorates seriously using NLOS satellite. Because of obstacles between NLOS satellites and GPS antenna, electrical waves omitted from GPS satellites are reflected or diffracted by obstacles. We propose the method to detect the obstacle using a fish-eye camera image to detect NLOS satellite. Firstly fish-eye image is parted into various small segments by k-means clustering method. And the segments are divided into sky and obstacle areas according to its movement using SIFT matching. The result of a field experiment shows the proposed method is effective to detect GPS-NLOS satellites.

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Most of robots has link mechanisms consisting of several links and joints, and the joint angle sensors are used to measure the poses. If any one of joint angle sensors breaks down, the robot cannot know its correct pose and can not move correctly. And, if there is a gap between the true value and the sensor value of the joint angle, the robot can not also know its pose. So, if the joint angles and the pose can be estimated from a camera image, the robot can solve the above problems and be controlled without joint angle sensors. In this paper, we propose an estimation method of robot manipulator's poses by only a RGB-D sensor without joint angle sensors. In the proposed method, the 3D model of the robot is compared with the acquired RGB-D images, and the joint angles are estimated by using the depth information and the color information. The proposed method was verified by using a multifingered robot hand.

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This research aims at construction of a highly accurate three-dimensional environmental map. In recent years, the compact and inexpensive RGB-D camera is used in various fields, and is applied also to sensing of the autonomous mobile robot. Generally, RGB-D camera is used for motion recognition of human beings, such as motion capture, and these applications do not need accuracy. Because the depth information of RGB-D camera is not accurate, it is unsuitable for highly accurate measurement to use. Therefore, distortion occurs on the three-dimensional environmental map constructed using RGB-D camera. We considered the calibration method of RGB-D camera for the purpose of acquiring accurate depth information.

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In our previous paper, we found that adding vibration to the thumb side shortened the perceived collision distance than adding vibration to the little-finger side. In this paper, we conducted similar experiment with changing the real distance between the palm and the object, to see the effect of real distance to this phenomenon. The experimental results showed that perceived collision distance shortened regardless of the real distance, but may be more easily induced when the object is placed far from the palm.

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In this paper, we report a work for investigation that whether or not depth of texture affect tactile feeling in the case that the textures on the surface are same. For making tactile feeling plates with variation of depth of hollows in texture on surface, photoresist is used. Through examinations by using the tactile feeling plates, we believe that depth of texture affect tactile feeling. Then, we consider why the depth of texture affect tactile feeling, even though textures on the surface of those plate are same.

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Highly sensitive, wide-measurement-range compact load sensors are desirable for various applications. A load sensor using an AT-cut quartz crystal resonator (QCR) has superior characteristics such as, high accuracy, improved strength under compressive stress, long-term stability. However, a retention mechanism is required to firmly support the QCR because the QCR is easily broken by stretching and bending motions. Conventional machining processes are not suitable for further miniaturization of the sensor. Even if the retention mechanism were miniaturized, the assembly process is complicated. We proposed a μQCR load sensor that fabricated by microfabrication and bonding for simplifying assembly process. The objective of this study is to improve the maximum load and load-measurement resolution of the sensor for application to biological signal detection in the bed. We fabricated a μQCR sensor with a sensitivity of 374 Hz/N (theoretical maximum load is 130 N) and succeeded in detecting multiple biological signals (respiration, heartbeat, and posture).

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The tactile information is very important for medical front. In order to obtain tactile information even in an area where human cannot directly contact. This paper present 3-axis force sensing system attachable to flexible fiberscope utilizing high elastic fabric; panty stocking fabric. The system uses force visualization mechanism. Using elastic fabric, the system get many advantages. The main features are not usage of electrical signal, small size, low cost, high sensitive, and what three dimensional force can be measured. The main target application is neurosurgical examinations, but the system would be useful for other medical and non-medical examination using fiberscopes.

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This paper describes a technique to provide tactile sense to a desk by a simple mechanism. The tactile sense is provided to the whole body of the desk by fixing a force sensor on each leg. One of the advantages of this technique is that the contact point can be estimated without any sensor device on the surface of the desk. The desk can be used as a kind of a haptic interface by utilizing the advantage. Some examples of application using the desk with computer graphics are introduced.

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This paper presents the fingertip which can detect the characteristic of object. In previous work, our research group found the sign for fracture appears before total fracture of the object when compressing ductility objects (such as Tofu) with fingertip filled with viscoelastic fluid. The sign is small change rate of pressure inside the fingertip. We call it "Initial break". However, the detail of the phenomenon was unclear. In this paper, we experimentally examine which conditions of fingertips affect expression of initial break.

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Humans can perceive external forces applied on a grasping tool based on skin pressure distribution at multiple contact areas during grasp. We have developed the TAKO-Pen, a pen-type pseudo-haptic interface using suction pressure stimulation on the each skin. In this paper, we investigate an improved method of skin stimulation based on a combination of psychophysical evaluations and mechanical simulation. We focus on a simplification method of the complex strain energy density (SED) distribution at the contact areas with a four quadrant values (SED index). The relationship between suction pressure and SED index was achieved by connecting the evaluations and the simulation. Moreover, we confirmed that an appropriate SED index could represent the magnitudes of forces in multiple directions with a linear function. Experimental results also showed that the proposed method could represent arbitrary directions between a pair of the orthogonal axes.

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In recent years, robots which have flexible tactile sensors to contact with a human and environment have been studied. However, these sensors face problems that the flexible material is unstable and the dead zone emerges by damage of interactions. On the other hands, a magnetic-type tactile sensor can cope with the problems by mechanically separating sensing elements from the contact layer. We propose a new magnetic-type tactile sensor which replaces the contact layer by magnetorheological elastomers. An advantage of this sensor over existing ones is that it does not need to include permanent magnets in the contact layer. This feature enables us to develop a whole-body tactile sensor since we do not need to consider the position of magnets and a curvature of the frame. This paper reports our prototype sensors and experiments to examine the reaction profile of the sensors.

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In this study, we develop a novel type of sensor, which is named HIGEMOJYA sensor II (HIGh Efficiency MOustache-Jungle-like YAbbcr Sensor II). This sensor is made by a large number of hairy tactile sensors, whose lengths change in a comparable wide range. We use this sensor to investigate the reaction of the sensor when an obstacle approaches it and keep the experiment records. We successfully make shape discrimination of the obstacle based on the reaction of the sensor.

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This paper discusses an effective sensing strategy for identification of contact conditions by active force sensing. The contact conditions include contact point, contact type and contact direction. To improve the speed and precision of distinction of the contact type in contact transition, we propose a sensing strategy for its transition detection. Two detection conditions are added to our previous method. One is the condition switching from Strategy III to Strategy II. Another is the consideration of contact point transition in the strategies. Effectiveness of our proposed method is verified through experiments.

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An apparatus to assist elderly patients to stand up, as well as for the upper body to lean forward, has been developed. The mechanism of the apparatus enables to shift the person's center of gravity along an adequate trajectory during the standing up process, so as not to cause strain on the joints of the user's leg. On a basis of this concept, a bed type which supports from the back of the user was developed. To verify the validity of the apparatus, we performed interviews and measuring experiments of the body motion and of the center of gravity. We also found that checking both trajectories was important to the comfort of the subject. From the results, by using these apparatuses, the user can stand up easily and our hypothesis was confirmed.

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There are people who can't transfer on their own and needs help for the move from a sitting posture to other sitting posture. However, many of them want to transfer without assistants. Therefore, we developed a robot that assists them to transfer on their own. In this investigation, we build the prototype of transfer unit for transfer assist robot. This prototype has the variable mechanism of ground area. This mechanism can raise stability of transfer assist due to open ground area and extend moving area due to close ground area. Based on motion experiments of the mechanism, it is shown that the proposed effective mechanism which designed as transfer unit for transfer assist robot.

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In recent years, the aging problems in Japan have been very serious. On the other hand, Smartphone have been infiltrated Japanese society. Operating system called Android is provided free by Google which many mobile phone manufacturers use on Smartphone and tablet PC. Therefore we develop the truck robot controlled by Smartphone which support people's lives. Our system consists of Smartphone, wireless camera and truck robot. Smartphone is connected on wireless camera at Wi-Fi and can display the view sent from wireless camera. Users can operate the robot from Smartphone. Our truck robot has three omni wheels and ultrasonic sensor on 3 places, so it can move 8 directions.

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