We propose a novel adsorption pad for wall climbing robot and irregular surface object using capillary force and water sealing. We call this adsorption pad as Super Wet Adsorption pad. The SWA pad has a porous part and a capillary part. The porous part is made by salt reaching method. When the SWA pad adsorbs to the wall which some sand and dust are attached, water comes from the porous part to avoid vacuum breaking. The capillary part is connected to the porous part to supply and stock the water. In this paper, we show the design of the porous part and the capillary part, fabrication process of each parts, and perform the evaluation experiment of the capillary force and adsorption of uneven surfaces, demonstration of wall climbing robot and adsorption of irregular surface foods.

This paper describes a octo-rotor unmanned aerial vehicle (UAV) with one degree of freedom (DoF) manipulator for bridge inspection. The UAV has an ability to contact bridge pier to conduct hammering test. To control contact force applied by the UAV to the bridge pier, one DoF is enough for the manipulator implemented on the UAV. A preliminary experiment shows that the force is proportional to the pitch angle of the UAV when it contacts the bridge pier. A bridge pier contact experiment shows that our developed UAV can control contact force between its end-effector and the bridge pier; mean error of the contact force is 4.27 ± 3.64 [N] against 20[N] desired force.

In this paper, we propose a new method to assemble microstructures with biological cells towards in vitro 3D cellular structures. The proposed assembly method uses self-assembly process of magnetized toroidal microstructures. Biocompatible toroidal hydrogel microstructures are prepared by electrodeposition method, and ferrite particles are put on the fabricated structures using poly-L-lysine (PLL). The microstructures are magnetized by the magnetic field at 3 T, and assembled by the magnetic self-assembly process. Biological cells were encapsulated in the microstructures and cultured to achieve high density of cells inside structures. The magnetized microstructures were assembled automatically. The magnetic force generated from the ferrite embedded microstructures was estimated and compared to the fluid resistance applied to the microstructures. The proposed method can be applied to achieve 3D in vitro cell structures with vascular networks for tissue engineering applications.

Single cell analysis has attracted much attention for revealing detailed and localized biological information. A local environmental control technique is desired when analyzing the detailed and localized properties of single cells. In this paper, we propose a local environmental stimulation system with micro dual-pipettes to stimulate the local reagent concentration dynamically, freely and automatically. When the local environment is controlled with chemical stimuli, the chemical solution is diffused and affects other objects. The local environment stimulation system with micro dual-pipettes can solve this problem by using spout pipette and suction pipette. As a cell analysis system, system quantification is necessary, so we try to realize it using a fluorescent substance. First step, we try to measure and control the light intensity. As an application of the system, the system can construct two-dimensional cell-organization by peeling off certain area of cell-sheet. Therefore, we try to control the area of peeling off cells using the system.

This paper presents a fabrication method of multi-graphene box structure by a nanomanipulation in a Field Emission Scanning Electron Microscope (FESEM). To bend the multi-graphene in plastic deformation region, the bending stress were measured using a silicon cantilever based on the nanomanipulation. In this study, defects were introduced inside the multi-graphene on the folding line of the multi-graphene by irradiating an electron beam assisted with oxygen gas. From experimental bending stress measurement, the bending stress was dropped with electron beam irradiation in oxygen gas environment. The fabrication of 3D box structure of multi-graphene was demonstrated from a cubic net of multi-graphene which was fabricated by a Focused Ion Beam (FIB) etching process. For bending the one side of the cubic net graphene, a tungsten probe was used after reforming by FIB etching as end-effector of nanomanipulator. The multi graphene was bent to form a box structure in 3D space.

Single cell analysis has attracted much attention to reveal the localized biological information in detail. Local environmental control technique is developed to analyze the localized detail properties of single cells. In this paper, we propose the local environmental chemical stimulation system with micro dual pipettes to stimuli the local reagent concentration dynamically and automatically. Local environmental chemical stimulation by dual pipettes is applied to the rotational speed control of bacterial flagellar motor, which is a rotary molecular machine. Here, we show quick response and rotational speed control of Na-driven flagellar motor in both accelerating and relaxing directions was demonstrated by automatic switching the local spout between Na-containing and Na-free solutions with dual pipettes. It was shown that the rotational speed could be maintained by automatic controlling the spouting velocity of Na-containing and Na-free solution with multiplying the applied DC voltage. Furthermore, it was confirmed that by applying the P-control, rotational speed of flagellar motor could be controlled more stably.

This paper presents a chip containing a flexible scaffold which facilitates the construction of tissues with different shapes. The chip, entirely made of Polydimethylsiloxane (PDMS), has 2 main components including actuator and channel layers. The actuator layer consists of a 6×6 array of membrane actuators, with round shapes. The channel layer has a single layered structure due to the simplicity in chip assembly and the ability to observe seeded cells via a microscope. The actuator array offers a flat surface, like a normal cell culture dish, in the rest state, while it temporarily offers a scaffold structure when actuators are activated. By changing the actuation pattern, formation of many scaffold structures is possible. To demonstrate the utility of this chip in biological application, a syringe pump is connected to all actuators to produced 2 different scaffolds, enabling the fabrication of multiple flat round and lattice shaped tissues. NIH3T3 cells with the amount of 5×106were seeded on the scaffold and kept inside the incubator for 24 hours. The 25 round shaped tissues with an average diameter of 623.87 μm were simultaneously fabricated when a scaffold with large deformed actuators was used. The lattice shaped tissue with a line width of about 300 μm was also fabricated with a different scaffold structure which has less actuator displacement. Results suggest the potential usage of this chip for the preparation of many building units with different structures, without the necessity of making a new mold for a new tissue shape.

Single cell analysis has attracted much attention for revealing detailed and localized biological information. A local environmental control technique is desired when analyzing the detailed and localized properties of single cells. In this paper, we propose a local environmental stimulation system with micro dual-pipettes to stimulate the local reagent concentration dynamically, freely and automatically. When the local environment is controlled with chemical stimuli, the chemical solution is diffused and affects other objects. The local environment stimulation system with micro dual-pipettes can solve this problem. By using spout pipette and suction pipette, it is possible to use local stimuli without affecting other objects. For evaluating the locality of the system, we use a fluorescent substance and measure the diffusion of the spouted solution.

In this work, we present a high-speed pick-and-place method for cell-assembly applications. Besides range of motion and accuracy, rapidness of a manipulation system is an important parameter, which is so far underrated in related studies. To achieve high-speed micromanipulation, obtaining 3D positions of both the target microobject and the end effector rapidly is necessary. In addition, controlling the vibration of the end effector, which is greater at high speed, is another arduous task. We propose a new fast detection algorithm for both the target microobject and the end effector for achieving high-speed control of the system. Moreover, to realize the stable control for very fast movements, the vibration of the system is compensated. High-speed control of the microhand system is demonstrated with preliminary experiments consisting of pick-and-place actions of 40 to 60 μm microspheres; we aimed at performing a manipulation task in 1 second. Comparison with similar studies shows the merit of the proposed automated high-speed micromanipulation system.

In this research we present a non-invasive Brain-Machine Interface (BMI) system that allows patients with motor paralysis conditions to control electronic appliances in a hospital room. The novelty of our system compared to other BMI applications is that our system gradually becomes autonomous by learning user actions (i.e. turning on/off window, lights, etc.) under certain environment conditions (temperature, illumination, etc.) and brain states (i.e. awake, sleepy, etc.). By providing learning capabilities to the system, patients are relieved from mental fatigue or stress caused by continuously controlling appliances using a BMI. We present an interface that allows the user to select and control appliances using electromyogram signals (EMG) generated by muscle contractions such as eyebrow movement. Our learning approach consists in two steps: 1) monitoring user actions, input data from sensors distributed around the room, and Electroencephalogram (EEG) data from the user, and 2) using an extended version of the Bayes Point Machine approach trained with Expectation Propagation to approximate a posterior probability from previously observed user actions under a similar combination of brain states and environmental conditions. Experimental results with volunteers demonstrate that our system provides satisfactory user experience and achieves over 85% overall learning performance after only a few trials.

Recently, with the development of life science field, micromanipulation technology has attracted attention. A two-fingered microhand system, that has been developed as a micro manipulator, can perform dexterous cell manipulation such as grasping, rotating, and transferring using two end effectors in a chopstick-like motion. The automated manipulation uses processing results based on all-in-focus (AIF) images and depth map obtained from the vision system; however, errors in the results still reduce the efficiency of the system. In this study, we introduce an automated grasping system that corrects the image processing error using the reaction force from the target object during grasping maneuvers. In our improved microhand system, micro force sensors that comprises strain gauge are attached to the two fingers of microhand. The two fingers with micro force sensor are set to be able to measure the horizontal and vertical forces to detect grasping state, precisely. Using the sensor information and the image processing results, we demonstrate that this system improves the accuracy and success rate of automated grasping.

In the fields of medicine and biology, it is essential to realize fine manipulation. Therefore, micromanipulation techniques and micromanipulators such as microgrippers and optical tweezers have been developed. We have developed a two-fingered microhand which is using the parallel mechanism to realize precise and stable micromanipulation. However, the previous microhand has problems about workspace and vibration. In this paper, the development of a new microhand which solves problems of previous microhand. The characteristic of new microhand is to enlarge the workspace utilizing the singularity of the parallel mechanisms. Inverse kinematics and structural analysis are used to analyze the workspace, and we show that results of two analyses match. Vibration analysis simulates transportation task and grasping task for manipulation. The new microhand has a potential to reduce the vibration by vibration analysis results.

Keyframe selection is the process of finding a representative frame in an image sequence. Although mostly known from video processing, keyframe selection faces new challenges in the lifelog domain. To obtain a keyframe that is close to a user-selected frame, we propose a keyframe selection method based on image quality measurements and excitement features. Image quality measurements such as contrast, color variance, sharpness, noise and saliency are used to filter high quality images. However, high quality images are not necessarily keyframes because humans also use emotions in the selection process. In this study, we employ a biosensor to measure the excitement of humans. In previous investigation, keyframe selection using only image quality measurements yielded an acceptance rate of 79.70%. Our proposed method achieves an acceptance rate of 84.45%.

We propose a social navigation model that allows a robot to navigate in a human environment according to human intentions, in particular during a situation where the human encounters a robot and he/she wants to avoid, unavoid (maintain his/her course), or approach the robot. Avoiding, unavoiding, and approaching trajectories of humans are classified based on the face orientation on a social force model and their predicted motion. The proposed model is developed based on human motion and behavior (especially face orientation and overlapping personal space) analysis in preliminary experiments. Our experimental evidence demonstrates that the robot is able to adapt its motion by preserving personal distance from passers-by, and approaching persons who want to interact with the robot. This work contributes to the future development of a human-robot socialization environment.

In order for robots to be a part of human society, their social accceptance is an important issue if smooth interaction with humans is to be achieved. We propose a modified social force model that allows robots to move naturally like humans, based on estimated human motion and face pose. We add to the previous model the effect of the force due to face pose, in order to predict human motion and compute the robot motion itself. Our approach was implemented and tested on a real humanoid robot in a situation in which a human is confronted with a robot in an indoor environment. Experimental results illustrate that the robot is able to perform human-like navigation by avoiding the human in a face-to-face confrontation. Our system provides accurate face pose tracking that allows a robot to have a more realistic behaviour compared to the original social force model.

For an object recognition task in an unknown environment, we propose a novel approach for illumination recovery of surface with cast shadows and specularities by using the object spherical spaces properties. Robust objects recognition in complex environment is fundamental to robot intelligence and manipulation. The proposed method is done for reducing the illumination effects on the objects detection and recognition processes. In this work, objects reference images are regenerated to match the scene lighting environment to increase the success rate of the recognition process. First, a database is generated by computing the albedo and surface normals from captured 2D images of the target objects. Next, the scene lighting direction and illumination coefficients are estimated. Finally, by using the calculated spherical spaces properties we regenerate objects reference data to match the search area illumination condition. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other techniques, our work requires no 3D models for the objects training process and takes images from a single camera as an input. Using our proposed 2D Spherical Spaces experimentally showed noticeable improvements in an objects identification task performed by an autonomous robot in a harshly illuminated environment.

We present our method for learning object categories from the internet using cues obtained through human-robot interaction. Such cues include an object model acquired by observation and the name of the object. Our learning approach emulates the natural learning process of children when they observe their environment, encounter unknown objects and ask adults the name of the object. Using this learning approach, our robot is able to discover objects in a domestic environment by observing when humans naturally move objects as part of their daily activities. Using speech interface,the robot directly asks humans the name of the object by showing an example of the acquired model. The name in text format and the previously learnt model serve as input parameters to retrieve object category images from a search engine, select similar object images, and build a classifier. Preliminary results demonstrate the effectiveness of our learning approach.

The aim of this study was to compare a robot designed using a virtual reality (VR) system (termed VR robot) with a real robot by using a psychological evaluation to investigate whether the VR robot can be used in the same manner as a real robot. To make the direct comparison between a VR and real robots possible, the same designed robots in both VR and real are used in the experiment. For evaluating the robots on a psychological basis, we focused on six basic dimensions (Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness) that ordinary people generally use to perceive robots. Sixty-one participants observed and evaluated a real and VR humanoid robots using a psychological scale. Results show that the real robot was evaluated to have higher scores for Utility, Possibility of communication, and Objective hardness and lower ones for Controllability as compared to a VR robot. The Vulnerability scores of the real robot and the VR robot were not significantly different. The usability of a VR robot is discussed in the paper.

The ability to recognize novel items in complex environment is fundamental to robot intelligence and manipulation. In this work, we consider the issue of segmenting visual and physical aspects of novel objects of interest, specifically ones that are being seen for the first time and located in the proximity of unidentified obstacles. Illumination at different wavelengths and angles are projected by a robot, thus acquiring additional information about the scene and exploiting it for successful novel objects segmentation. By analyzing shades and reflections of a scene's objects, we were able to form and identify true edges and visually separate items of interest. In order to recognize the physical characteristics of segmented objects, we introduce a novel material classification technique which utilizes static electricity charge sensing. Our proposed methods do not require predefined models of target objects and assume no previously assigned targets' pose. Using extracted object visual and physical aspects, an autonomous robot manipulator successfully performed a trash separation task.

In the field of bioscience, such as regeneration medicine and cloning, the manipulation and analysis for cells are performed by many researchers. However, manual operation for such micro objects is not feasible and practical for beginner operators. As for the problem, we have developed a two-fingered microhand supporting manual operation. Using the microhand, we can manipulate cells i.e., grab, rotate, carry, and so on - like when using chop sticks. The stiffness measurement of a cell is a key approach in single cell analysis techniques. It is important in indicating cell condition, because the stiffness of a cancer cell is lower than that of a normal cell as an example. However, measuring stiffness is very difficult, because deformations of cell are plasticly, and many researches to measure the stiffness of cell don't deal with plastic deformation. So, in this paper, the cell hardness is calculated instead of cell stiffness by measuring the reaction force caused in the process of cell deformation via a micro force sensor attached to the end-effector of the microhand. Our results point out that this can be one efficient measurement method for acquiring cell hardness. In this paper, three topics are discussed. First one is the fabrication of the end-effector with micro force sensor. Second one is the method of measuring hardness of cell. As a last one, the hardness of the fibroblastic cell is measured by proposed method and the effectiveness of the proposal technique is shown.

For potential applications in bioscience, a two-fingered microhand with dexterous manipulation capability was developed. This microhand system could perform dexterous tasks such as cell rotation, single cell pick-and-place, cell patterning, and measurement of mechanical properties of living cells. However, it is a tedious task to manipulate micro objects manually. In order to improve the efficiency of the system, automated micromanipulation is required. This paper describes how to automate micromanipulation for this two-fingered microhand so that it can perform desired tasks more efficiently, more accurately, and faster. By integrating an All-In-Focus imaging system to the microhand system, 3D positions of the two microfinger tips and micro target objects can be obtained. These 3D positions are necessary for the microhand to handle the target object automatically. We demonstrate this capability by a pick-and-place task with multi-sized microspheres. Short time for object grasping and success rate over 70% for all cases could be achieved.

In this study we explored basic dimensions used to perceive humanoid robots and developed a scale to evaluate perception of humanoid robots, PERNOD. Previous studies of perception of humanoid robots used psychological scales created for interpersonal perception between humans. This study clarified the basic dimensions of perception of humanoid robots and developed PERNOD by means of psychological methodology. The results revealed six basic dimensions of perception of humanoid robots: Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness. The 6 dimensions of PERNOD were originally developed for humanoid robots. Thus, these dimensions represent the organization of knowledge used in the recognition of humanoid robots. Usability of PERNOD was discussed.

New gait planning using a nonholonomic model with difference equation constraints is proposed for biped robot walking. A model of a pivoting telescopic segment is used as the kinematic foothold selection model of a bipedal robot. The repetitive and discontinuous constraints of pivoting, expanding, and contracting make up the set of walking trajectory data. The k-step reachable region is defined as the set of the k-th state that the system can reach from the initial state, and the motion planning is solved using the Jacobian matrix of the state with regard to the input series. The difference equation constraints can be discussed as a digital control of continuous-time nonholonomic systems. The gait planning is modified based on the limiting condition for the HRP-2 humanoid robot. Energy consumption is evaluated based on the linear-pendulum model and the gait planning is optimized. The feasibility of the proposed walking planning is demonstrated through a numerical simulation and an experiment involving the HRP-2 humanoid robot.

A new method for bipedal walking on rough terrain by using ZMP criteria map is proposed. The rough terrain walking is classified to “step up” and “step down” by landing timing of a swing leg. The walking pattern is modified in real-time according to the difference between the ideal timing and the measured timing by a force sensor on the foot. In the case of “step up”, the landing timing is faster than the ideal, and the swing leg trajectory should be change to follow the step so that the ZMP based balance of the sudden caused double support phase is kept. In the case of “step down”, the landing timing is later than the ideal, and the swing leg trajectory should be change to seek the ground so that the balance of the unknown future double support phase is kept. The modified walking pattern is decided based on the ZMP criteria map. The ZMP criteria map can indicate a safe landing timing and landing position of a swing leg. By referring the ZMP criteria map, the robust walking pattern can be planned. The proposed method is implemented to HRP-2, and the effectiveness is confirmed through experiments.

Finding objects and tracking their poses are essential functions for service robots, in order to manipulate objects and interact with humans. We present an approach for object detection and 3D pose estimation for autonomous mobile robots, that is suitable for general uses in a modularized robot control system. Our approach extracts local features from the input images, searches for the reference pattern, and then produces the 3D pose in camera coordinate system, using only a single reference image and the 6-DOF pose in it. We have created an RT (Robot Technology) component that can be used in any RT-based system, and developed an algorithm that can extend the range of detection and produce robust pose estimation. For evaluation, we have integrated our vision component in an autonomous robot system with a search-and-grasp task, and tested it with several objects that are found in ordinary domestic environment. We present the details of our approach, the design of our modular component design, and the results of the experiments in this paper.

A two-fingered micro hand has been available for use for years and allows dexterous manipulation of a single cell: grabbing, positioning, rotating and releasing. The end-effector of this micro hand consists of two glass needles; however, the glass tips must be finely adjusted and the micro hand must be calibrated prior to use. Because these initial procedures require highly skilled human operators and a great deal of time, a fine adjustment module (FAM) has been developed for assisting with the fine adjustment work and was successfully shown to make the initial setup easier. However, problems with the calibration process and with the dependence on a user of the FAM control are still present. One means of improving the system for users is to automate the initial setup. The detection of the glass tips in a wide range of Z directions from a microscopic image having a small depth of focus requires robust calibration and must be possible using an automated FAM control. From this perspective, the tip position detection algorithm using the evaluation function, Image Quality Measurement (IQM), is proposed in this paper. Based on this algorithm, the automated initial setup method is explained and its effectiveness is experimentally evaluated.

In this paper, we propose a sensor for detecting particles flowing in a micro channel fabricated with polydimethylsiloxane (PDMS) chip. A light source placed at one side of a micro channel irradiates the micro channel through plastic optical fibers (POF), and a detector placed at the opposite side of the micro channel receives light transmitted through the POF. Since this sensor simultaneously detects plural particles with a diameter of around 100 ¿m flowing in a micro channel, it can be implemented in automatic measurement systems of cells in desktop bio plant, on which automated embryonic cell manipulation is achieved using micro robotics technology.

A new convergence calculation method of the normal distributions transform (NDT) scan matching for high resolution of grid maps is proposed. NDT scan matching algorithm usually has a good effect on large grids, so it is difficult to generate the detailed map with small grids. The proposed method employs interactive closest point (ICP) algorithm to find corresponding point, and it also enlarges the convergence area by modifying the eigenvalue of normal distribution so that the evaluation value is driven effectively for the pairing data. In addition, outlier elimination process is implemented to the scanning for sub-grid scale object. The scanning data from laser range finder (LRF) have error but its set of detected small object can be clustered to determine the center of mass (CoM) and the outlier data. The outlier commonly locates behind true points and it can be eliminated when the robot observes from other point. Experimental result shows the effectiveness of the proposed convergence algorithm and outlier elimination method.

In this paper, we presented a design for an automated cell supply system that can be used with complex microfluidic applications requiring single cell loading such as the current nuclear transplantation method. The aim of the system is to automatically transfer mammalian donor (~15 ¿m) or egg (~100 ¿m) cells one by one from a container to a PDMS micro-channel and then transport them to other modules. The system consists of two main parts; a single cell suction module, and a PDMS-based microfluidic chip controlled by an external pump. The desired number of vacuumed cells can be directed into the microfluidic chip and stored in a docking area. From the batch, they can be moved to next module by activating pneumatic pressure valves located on two sides of the chip.

Recently, human-friendly robots such are mainly focused on their functions. And, based on these functions, many researchers have tried to realize good applications for convenient human life. While, a mental safety and affinity for human are also important topics to co-existence with robots. The evaluation techniques of robot motion and design are necessary to consider the above things. However, the costs of real robot are very expensive. So, it is difficult to evaluate human impression for several real robot. So, to solve this problem, we have focused on the evaluation techniques by using virtual reality. In the previous work, several types robot design were evaluated on virtual reality by using meta model, which is abstraction model of robots. When researchers want their robot to reflect an evaluation result on virtual reality, there are some relationships between virtual robot and real one. If there is no relation from real robot and virtual one, we cannot do any feedback to real robots based on virtual one's results. In this paper, we evaluate the relationships between virtual robot and real one based on human impressions through several experiments.

To make structured environment aims at establishing the information structured environment which enables robots to get information and knowledge necessary to carry out the given tasks from the environment. In this paper, we build the information structured environment named the u-RT space, and then design and control the librarian robot system based on the proposed environment, which can put books on the proper slot in the bookshelf using the ambient intelligence and the book information. First, we introduce the information structured space where the physical space and the virtual space are connected each other, and propose the robot localization method and the bookshelf information system based on the ambient intelligence realized by the RFID technology. Next, we introduce the librarian robot system which consists of the manipulator which can recognize and manipulate books, and the mobile platform which can localize itself and navigate using the ambient RFID tags implanted under the floor even if there are high bookshelves. Then we propose the classification and integration method of the information from various ambient sensors which enables the proposed robot to complete given missions successfully. Finally, the performance of the proposed librarian robot system is evaluated by the experiment based on an example scenario in the u-RT space.

In this paper, a novel approach of knowledge management for the space/location perceiving capacity of robots is proposed. First, the ubiquitous function services composed of smart object, smart logic, and smart discovery service are proposed in order to distribute knowledge flexibly and reliably to changing environment and also for a robot to invoke and merge the distributed knowledge more freely. Next, physical and virtual spaces are merged by RFID tags. Through this, it is shown that ambient intelligence is realized and the space localization and mapping problem of robots can be more easily solved. Finally, the experiment based on an example scenario is carried out to verify the proposed method in the informative space named u-RT space which has two kinds of RFID tags, a virtual space with ubiquitous function services realized by Web services, and a networked robot system which works in these spaces

In this work, we propose a new framework for better deployment and utilization of robots in our uncertain, unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with many challenges in the user programming, this work is to provide an open environment for building robot programming automatically, where we have robots learn how to accomplish commanded tasks interacting with the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided by the robot manufacturer. The main contributions of this work is to develop the knowledge integrator platform that we call Omniscient Organizer that generates the application programs and send them to the robot controller through networks. In the Omniscient Organizer, the object-related information downloaded from the object Web server merges into robot control software based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform common household tasks such as clearing the table within the proposed framework.

The goal of this paper is to realize a hands free operating system for analytical work on protein crystal using a micro hand and an integrated vision system. At first, the operation for the protein crystal analysis is summarized to make it clear what kind of tasks should be necessary for automatic operation. Secondly, the proposed system is briefly reviewed, which is constructed with a two-fingered micro hand system and an all-in-focus microscopic system. Thirdly, a new localization criterion for transparent objects with the all-in-focus system is proposed for the protein crystal operation. Finally, experimental results show the validity of the proposed system and algorithm.

This paper describes the technique to grasp the micro transparent objects, such as crystal and cell, using the integrated vision system. At first, several 3D modeling techniques for transparent object are surveyed, which were mainly applied to use the polarization technique. Secondly, polarization characteristics on micro transparent object are evaluated. Thirdly, integrated vision system for micro objects is briefly reviewed. Then, to solve the problem of the transparent object with this integrated vision system, several new methods based on the volume rendering and edge methods information using the integrated vision system is proposed. Finally, the modeling and handling technique are proposed.