並木 明夫

In this study we successfully demonstrated a dexterous manipulation of sheet-like elastic objects - namely, playing cards - using a high-speed multifingered robot hand system. Our goal in this research was to achieve card flicking by vibrating a fingertip of the robot hand at high speed. Firstly, we discuss card grasping in the initial state based on the geometrical conditions of the card and the kinematics of the robot hand. Secondly, we propose a strategy for performing the card flicking. In addition, we obtain the card-flicking conditions by analysing the slip between the card and the fingertip of the robot hand. In addition, we analyse an energy transition of the card based on the physical law. Thirdly, we estimate a spring constant of the card via a vibrational experiment. Then we simulate the trajectory of a flying card after the slippage, and compare a simulation result with an experimental result of the flying card's trajectory. Finally, we show the experimental results of card flicking using the high-speed robot system and the proposed method.

In recent years, the demand for robots to perform various tasks in dangerous environments has increased. Master-slave type robots are more suitable for dangerous environments than autonomous robots because human operators can give proper judgement. And unilateral type master-slave control with a simple and lightweight master device has advantages of quick and responsive operability. However, autonomous assist control to the slave robot should be added because direct force feedback is not available in such systems. In addition, virtual assist feedback to the human operator is useful for quick operation. In this study, some assist control methods for safety and operability improvement are proposed. Finally, experimental results are shown, and the validity of the proposed system is verified.

In this study, we propose a novel air-hockey robot that can select the optimal actions according to the behavior of an opponent human player. The attack behavior of the robot is optimized during an air hockey game by recognizing the motions of the puck and the human hand. First, we explain how to calculate the attack position. Second, we explain the algorithm for decision making using an attack value based on the puck and the position of the human hand. The attack value is calculated by considering the physical constraints of both the attack and defense sides. Then, we show experimental data and explain the reason for robot behaviors based on the calculated attack value.

In robotic manipulation, visual servoing is an important technique for achieving dexterous and accurate handling of objects. One of the most important problems in this task is occlusion by the robot's body. In some situations, it is difficult to know the position and orientation of the object during manipulation because it is hidden by the robot itself. If its position and orientation could be estimated by considering this occlusion, the robot would be able to manipulate it by visual servoing more dexterously. In this paper, we propose an algorithm for estimating the position and orientation of the manipulated object during manipulation by using a 3-D sensor. 3-D information of the total environment is observed by the 3-D sensor, and the observed 3-D point-cloud information is classified into the manipulator, the object, and the others based on their 3-D models. The proposed algorithm was verified in an actual robot manipulation system.

Paper folding is one of the most difficult tasks for multi-fingered robot hands because paper is deformable and its stiffness distribution is nonuniform. In this study, we aimed to achieve dexterous paper folding by extracting some dynamic motion primitives. Each primitive contains visual or force information, a physical model of a sheet of paper is used for analyzing its deformation, and a machine learning method is used for predicting its future state. We also propose a strategy for achieving valley folds in a sheet of paper twice in a row. One problem faced in folding paper is that, in the second fold, the crease line of the first fold disturbs the folding accuracy. We propose some new manipulation techniques to solve this problem. Finally, we show some demonstrations of paper folding achieved with a high success rate.

In recent years, various robot hands and arms have been developed for achieving dexterous manipulation tasks. However, there are few robots that are able not only to move quickly but also to handle tools dexterously. Motion in the Japanese game kendama is one example of dynamic manipulation and skillful handling. Although robotic kendma has been studied in the past, these robotic hands cannot be used effectively. The purpose of this study was to achieve kendama motion by estimating the object to be grasped based on a high-speed vision system and CoP tactile sensors. Our robot successfully performed the catching motion in kendama.

In this paper we suggest an entirely new strategy for the dexterous manipulation of a linear flexible object, such as rope or a cable, with a high-speed manipulator. We deal with a flexible rope as one example of the linear flexible object. The strategy involves manipulating the object at highspeed. By moving the robot at high-speed, we can assume that the dynamic behaviour of the flexible rope can be obtained by performing algebraic calculations of the highspeed robot motion. Based on this assumption, we derive a dynamic deformation model of the flexible rope and confirm the validity of the proposed model. Then we perform a simulation of dynamic, high-speed knotting based on the proposed model. We also discuss the possibility of forming the knot based on a simple analysis model. Finally, we show experimental results demonstrating dynamic, high-speed knotting with a high-speed manipulator. ©2013 Yamakawa et al.

In this paper we suggest an entirely new strategy for the dexterous manipulation of a linear flexible object, such as rope or a cable, with a high-speed manipulator. We deal with a flexible rope as one example of the linear flexible object. The strategy involves manipulating the object at highspeed. By moving the robot at high-speed, we can assume that the dynamic behaviour of the flexible rope can be obtained by performing algebraic calculations of the highspeed robot motion. Based on this assumption, we derive a dynamic deformation model of the flexible rope and confirm the validity of the proposed model. Then we perform a simulation of dynamic, high-speed knotting based on the proposed model. We also discuss the possibility of forming the knot based on a simple analysis model. Finally, we show experimental results demonstrating dynamic, high- speed knotting with a high- speed manipulator.

The purpose of this study is to perform a dynamic manipulation of a linear flexible object. As examples of the dynamic manipulation, shape controls and a dynamic knotting of a flexible rope are achieved by a high-speed robot arm. First, an entirely new strategy for dynamic manipulation of the flexible rope with the high-speed robot is introduced. The strategy is to manipulate the flexible rope with a high-speed motion. Moving the robot at high-speed, we assume that a dynamic deformation of the flexible rope can be obtained through algebraic calculations based on the robot motion. Based on this assumption, we propose a discrete deformation model of the flexible rope. As a result, we can obtain the robot trajectory from the desired rope configuration using the proposed model. Moreover, we discuss the validity of the proposed model based on the equation of motion of the flexible rope. Next, simulation results and experimental results of shape controls (rectangle and circle) are described. Finally, simulation result and experimental result of the dynamic knotting using a high-speed robot arm are shown as one application of the proposed method.

This paper demonstrates the relationship between the production process of a knot and robot hand skills. First, we define the descriptions (rope intersection and fixed position) of a knot. Next, the characteristics of the robot hand skills are clarified from viewpoint of the description of the knot. Then, in order to obtain the production process of knot, we propose an analysis method based on the structure of knot and the characteristics of the robot hand skills. And, we analyze various knots using the proposed analysis method. Finally, in order to validate the production process obtained by the proposed analysis method, an experimental result of half hitch is shown by using a high-speed multifingered hand system.

In this paper, we propose a new display system consisting of a high-speed vision and high-speed projector, which has remarkable features. First of all, this system generates projection images using simple image processing, because the projection image is controlled without three dimensional shape of an object. Secondary, in this system the projection image is controlled based on errors on the image plane with visual servoing techniques. By using this technique, this system can project images regardless of the pose of the object to be projected. Moreover, there is no need for precise calibration between the projector and camera. The last feature is that it utilizes high-speed vision. This feature makes it possible to control projected image in real time. Having these features, our proposed display system can project images not only on stable fixed screen but also on other objects such as deformable screens and moving screens. To validate the proposed system, we experimented by projecting on a moving screen as well as a bending screen.

In this paper, we propose an entirely new manipulation strategy for dynamic manipulation of a ribbon with a high-speed manipulator. The manipulation strategy involves manipulating the object at a constant, high speed. Then, we can assume that the dynamic behavior of the ribbon can be obtained by performing algebraic calculations of the robot motion using the proposed strategy. Based on this assumption, we derive a model of the ribbon and suggest a motion planning method using the proposed model. Finally, we show experimental results of shape control of a ribbon based on the proposed method.

In this study, we design a novel air-hockey robot system that switches strategies according to the playing styles of its opponent. The system consists of a four-axis robot arm and two high-speed vision sensors. We control the robot using visual information received at a rate of 500Hz. The control system consists of three layers: motion control, short-term strategy, and long-term strategy. In the motion control layer, the robot is controlled by visual information of the puck. In the short-term strategy layer, motion of the robot is changed according to the motion characteristics of the puck. In the long-term strategy layer, the motion of the robot is changed according to the playing style of the opponent. By integrating the three control layers, the robot exhibits human-like reactions, which increase the appeal of the game. Experimental results verify the effectiveness of our proposed method.

The purpose of this paper is to achieve a dynamic folding of a cloth using a robot system with two high-speed multifingered hands. First, we will analyze the dynamic folding by a human subject in order to extract elements for this task. Second, a simple model of sheet-like flexible object using high-speed motion will be suggested. Third, motion planning of the robot system will be performed based on the proposed model and a simulation result will be illustrated. Fourth, the folding analysis using a triple pendulum model will be carried out. Fifth, a high-speed visual feedback control method will be proposed to grasp the cloth. Finally, an experiment result with the motion planning and the high-speed visual feedback will be demonstrated.

This video introduces an ultra high-speed robot as a milestone in the history of intelligent manipulation systems. To develop the ultra high-speed robot under the concept of dynamics matching, we began with the development of a 1 kHz vision system. Next, we developed a sensory-motor fusion system by introducing the 1 kHz vision system. In addition, we have developed a new high-torque mini actuator and a highspeed multi-fingered hand with these incorporated. Integration of these components brings real-time dexterous manipulations unlike commonly-used control based on prediction or learning.

In this research, we successfully demonstrated dexterous manipulation of sheet-like elastic objects, namely, playing cards, using a high-speed robot system. In particular, our goal was to achieve card flicking by vibrating a fingertip of a robot hand at high speed and card catching by using highspeed visual feedback based on a high-speed vision system. We discuss card grasping in the initial state based on the geometry conditions of the card and the kinematics of the robot hand, and we propose a strategy for card flicking. We also suggest a card catching method based on information obtained by the high-speed vision system. In addition, we obtain the card flicking conditions by analyzing the slip between the card and the fingertip of the robot hand. Finally, we show experimental results of card flicking and card catching.

In this paper, we propose an entirely new manipulation strategy for dynamic manipulation of a flexible rope with a high-speed robot arm. The manipulation strategy involves manipulating the object at a constant, high speed. Then, we can assume that the dynamic behavior of the flexible rope can be obtained by performing algebraic calculations of the robot motion using the proposed strategy. Based on this assumption, we derive a model of the flexible rope and suggest a motion planning method using the proposed model. Finally, we show experimental results of rope deformation control based on the proposed method.

Humans can perform fast and skillful manipulations using various parts of the body by effectively utilizing the dynamics of the targets. Visual sensation is the most important human sense used for such manipulations. Juggling is one such example involving skillful and dynamic manipulations, and visual information is essential for it to be successful. Previously, there have been several studies about robotic juggling. However, none of these studies have considered cases in which a human-like multifingered hand-arm is used for the robotic juggling. The purpose of this study is to achieve two-ball juggling using our robotic hand-arm, which has three general purpose fingers, and stereo vision. Image processing is executed at 500 fps using a high-speed vision system and graphics processing unit (GPU). The trajectory of the robotic hand-arm is generated based on the ball's estimated dropping position and moment, and the robot catches the ball. The juggling motion is achieved by repeating this cycle. Therefore, the results show that the robot successfully juggles two balls using our hand-arm system.

This paper proposes a robot which can play air hockey game with a human. The robot consists of a 4-axis robot arm and a high-speed vision, and the robot is controlled based on visual information at a rate of 500[Hz]. The robot system has the abilities to adjust the strength level and to change the strategy based on the game situation. A system designer can easily adjust these abilities by setting several specified parameters. In this paper, first, a recursive trajectory generation using continuous images from high-speed vision is explained. Secondly, the response control to adjust the strength level of the robot is explained. Thirdly, the decision-making using AHP (Analytic Hierarchy Process) is proposed. This ability enable the robot to switch the game plan. Finally, we show the data of experiments and verify the effectiveness of the system.

In this paper, we propose an entirely new strategy for dynamic manipulation of sheet-like flexible objects. As one example, we consider dynamic folding of a cloth by a highspeed robot system consisting of two high-speed multifingered hands mounted on two sliders and a high-speed vision system. First, the dynamic folding performed by a human subject is analyzed in order to extract the necessary motion for this task. Second, a model of a sheetlike flexible object is proposed by extending a linear flexible object model (algebraic equation) using high-speed motion. Third, motion planning of the robot system is performed by using the proposed model, and the simulation result of the dynamic folding is shown. Fourth, high-speed visual feedback control is proposed in order to enhance the manipulation strategy. Finally, experimental results of the dynamic folding of the cloth by the high-speed robot system are shown. © 2011 IFAC.

This paper proposes a teaching system for multi-fingered robot hands by using kinetic information of target objects with visual feedback. The purpose of this system is to operate multi-fingered robot hands with high DOF mechanisms intuitively and effectively. The system calculates the appropriate trajectory of the fingers according to the kinetic information of the target object under the twist rolling contact constraint. In addition, force and visual feedback control is adopted for more accurate and stable manipulation. This paper describes the results of the experiments by using the developed teaching system, and the future works to be improved are discussed. © 2011 IEEE.

In this paper, the task of tweezers manipulation is considered with the goal of achieving dexterous manipulation of a human tool. First we analyze the contact state between fingers and tweezers in order to design preferable fingers for tool manipulation. Next the control method based on high-speed visual servoing is presented. Experimental results are shown in which a high-speed hand grasps a tiny grain with tweezers in 2-D and 3-D situations. © 2011 IEEE.

The purpose of the work described in this paper is to achieve dynamic manipulation of a sheet-like flexible object. As one example, we examine dynamic folding of a cloth with two high-speed multifingered hands mounted on two sliders. First, dynamic folding by a human subject is analyzed in order to extract the necessary motions for realizing this task. Second, a model of a sheet-like flexible object is proposed by extending a linear flexible object model (algebraic equation) that takes advantage of high-speed robot motion. Third, motion planning of the robot system is performed by using the proposed model, and the simulation results are shown. Finally, an experiment was conducted with the robot motion obtained by the simulation.

Recently, several types of high-speed vision in which the sampling rate is more than 1 kHz have been developed. In the high-speed vision system, not only sensing but also processing is achieved at high-speed, and it improves the performance of visual servoing. In this chapter, we described some examples of visual feedback control methods in our high-speed manipulation system. First, a hybrid trajectory generator using visual information is proposed for a batting task. In the method, the manipulator trajectory defined as a polynomial function of time is modified by visual information directly. Next, a visual servoing control with a passive joint problem is proposed for tool manipulation. Experimental results are shown. © 2010 Springer-Verlag London.

In this paper, we propose an entirely new strategy for dexterous manipulation of a linear flexible object with a high-speed robot arm. The strategy involves manipulating the object at high speed. By moving the robot at high speed, we can assume that the dynamic behavior of the linear flexible object can be obtained by performing algebraic calculations of the robot motion. Based on this assumption, we derive a model of the linear flexible object and confirm the validity of the proposed model. Finally, we perform simulation of dynamic knotting based on the proposed model. Results of an experiment demonstrating dynamic knotting with a high-speed robot arm are shown.

This paper proposes a new strategy for making knots with a high-speed multifingered robot hand with tactile sensors and visual sensor. The strategy is divided into three skills: loop production, rope permutation, and rope pulling. Through these three skills, a knot can be made with a single multifingered robot hand. In loop production, the wrist joint angle control is proposed by using visual feedback with high-speed visual sensor. In addition, the dynamics of the rope permutation are analyzed, and an effective tactile feedback control method is proposed based on the analysis. Finally, expe...

Vision is one of most important sensors for dexterous manipulation. The sampling rate of usual vision system is 30Hz. However, it is not enough to control manipulation system in realtime. In order to solve this problem, a high-speed vision system has been developed in which the sampling rate is more than 1kHz. In this paper, some examples of dexterous manipulation based on the high-speed visual systems are proposed. First, tool manipulation by multifingered hand is proposed, in which the calibration errors among the hand, the tool, and the target are compensated for in realtime by visual feedback. Next, flexible rope manipulation by a multifingered hand is proposed, in which the change of shape of the rope is observed by vision in realtime. Finally, dynamic regrasping using fingertip rotation mechanism is proposed. Experimental results are shown.

This paper illustrates the relationship between a knotting process and knotting skills for a multifingered hand. To determine the appropriate skills required for knotting, we analyzed the knotting motion performed by a human hand. The knotting process is divided into four handling skills. In addition, this paper proposes a new strategy for making knots with a multifingered hand. The strategy consists of several basic skills, and various knots can be achieved by reconfigurable synthesis of skills. Finally, we show experimental results of an overhand knot and a half hitch.

This video introduces the demonstration of skillful manipulation using a high-speed robot system. The system consists of visual and tactile sensors at a rate of 1 kHz and a high-speed hand-arm manipulator. The high-speed sensory-motor fusion improves not just the speed of existing robot manipulations, but robotic skills by introducing the features peculiar to high-speed motion. Based on such a concept, new variations of skillful manipulation were achieved.

To achieve a human like grasping with a multi-fingered robot hand, the grasping force should be controlled without using information from the grasped object such as its weight and friction coefficient. In this study, we propose a method for detecting the slip of a grasped object using the force output of Center of Pressure (CoP) tactile sensors. CoP sensors can measure the center position of a distributed load and the total load applied on the surface of the sensor, within 1 ms. These sensors are arranged on the fingers of the robot hand, and their effectiveness as slip detecting sensors is confirmed in tests of slip detection during grasping. Finally, we propose a method for controlling grasping force to resist tangential force applied to the grasped object using a feedback control system with the CoP sensor force output.

In this paper the robotic throwing task is considered with the goal of achieving high-speed dynamic manipulation. We propose a kinetic chain approach for swing motion focused on torque transmission. In addition the release method using a robotic hand is analyzed for ball control. Experimental results are shown in which a high-speed manipulator throws a ball toward a target.

In order to achieve as skillful handling as a human hand, it is necessary that a hand has the capability to manipulate tools. One important problem in tool handling with a multifingered hand is that the relative positions between the robot hand, the tool and the handled object change during the handling. For this reason, it is necessary to measure these relative positions in realtime, and to control the hand so as to cancel the changes. We have resolved this problem by using a high speed visual servoing. In this paper, as an example, a tweezers is handled by a multifingered hand. Further, a new method to control tools along with experiment result are shown.

In this paper, we examine the relationship between a knotting process and the individual skills of which a robot hand is capable. To determine the necessary hand skills required for knotting, we first analyzed the knotting action performed by a human subject We identified loop production, rope permutation, and rope pulling skills. To take account of handling of the two ends of the rope, we added a rope moving skill. We determined the characteristics of these skills using an intersection-based description. The knotting process was examined based on the analysis of knots and the characteristics of the robot hand skills. Finally, we show experimental results of an overhand knot and a half hitch performed using a highspeed multifingered hand system.

To achieve a human like grasping with a multi-fingered robot hand, the grasping force should be controlled without using information from the grasped object such as its weight and friction coefficient. In this study, we propose a method for detecting the slip of a grasped object using the force output of Center of Pressure (CoP) tactile sensors. CoP sensors can measure the center position of a distributed load and the total load applied on the surface of the sensor, within 1 ms. These sensors are arranged on the fingers of the robot hand, and their effectiveness as slip detecting sensors is confirmed in tests of slip detection during grasping. Finally, we propose a method for controlling grasping force to resist tangential force applied to the grasped object using a feedback control system with the CoP sensor force output.

This paper proposes a new strategy for making knots with a high-speed multifingered robot hand having tactile sensors. The strategy is divided into three skills: loop production, rope permutation, and rope pulling. Through these three skills, a knot can be made with a single multifingered robot hand. The dynamics of the rope permutation are analyzed in order to improve the success rate, and an effective tactile feedback control method is proposed based on the analysis. Finally, experimental results are shown.

In most previous studies, it has been difficult for a robot hand to regrasp a target quickly because its motion was static or quasi-static, in a constant contact state. In order to achieve high-speed regrasping, we propose a new strategy which we call dynamic regrasping. In this strategy, the regrasping task is achieved by throwing a target up and by catching it. In this paper, a regrasping strategy based on visual feedback is presented and experimental results using a high-speed multi-fingered robot hand and a high-speed vision system are shown. A cylinder is chosen as a specific example of target for dynamic regrasping, with which successful dynamic regrasping tasks are experimentally achieved.

We propose a tactile feedback system in real time using a high-speed multifingered robot hand and high-speed tactile sensor. The system is respectively capable of high-speed finger motion up to 180 deg per 0.1 s and high-speed tactile feedback with a sampling rate higher than 1 kHz. In this paper, we describe dynamic pen spinning as an example of a skillful manipulation task using a high-speed multifingered hand equipped with tactile sensors. The paper describes the tactile feedback control strategies and experimental results.

A hierarchical control architecture is proposed on the basis of an interaction model between efferent and afferent information in brain motor control. The model has five levels: motoneurons, premotor interneurons, pattern generator, parameter selection and action planning. The effectors including biophysical properties receive the commands from motoneurons. In the proposed architecture, the premotor interneurons and motoneurons are implemented as a servo module; the pattern generator corresponds to the motion planner; and the parameter selection is realized by adaptation module. The afferent information is the feedback signal and the efferent information corresponds to motion command and parameter adaptation. Grasping and handling of a dynamically moving object are implemented on a DSP network with a high-speed vision, a dextrous hand and a 7 DOF manipulator. The results show responsive and flexible actions that exhibit the effectiveness of the proposed hierarchical modular structure.

A hierarchical control architecture is proposed on the basis of an interaction model between efferent and afferent information in brain motor control. The model has five levels: motoneurons, premotor interneurons, pattern generator, parameter selection and action planning. The effectors including biophysical properties receive the commands from motoneurons. In the proposed architecture, the premotor interneurons and motoneurons are implemented as a servo module; the pattern generator corresponds to the motion planner; and the parameter selection is realized by adaptation module. The afferent information is the feedback signal and the efferent information corresponds motion command and parameter adaptation. Grasping and handling of a dynamically moving object are implemented on a DSP network with a high-speed vision, a dextrous hand and a 7 DOF manipulator. The results show responsive and flexible actions that exhibit the effectiveness of the proposed hierarchical modular structure.

A grasping algorithm that takes into account both visual and tactile feedback has been developed for a system consists of a multifingered hand and a vision. The grasping process consists of two phases: the non-contact phase, i.e. the approach of the robot hand on the object, is realized using visual information while the contact phase, i.e. the touch of the object by the robot fingers is made using both visual and tactile information. To achieve these two processes we present an original algorithm that allows a multifingered hand to grasp an object using visual and tactile feedback. In this...

This study has attempted to develop a prototype of a master-slave manipulation system with a force-feedback function for use in remote endoscopic surgery. The slave manipulation system uses a forceps system which is capable of being opened and closed by a motor-and-wire-driven arrangement, and which is located at the head of a robot arm system. The master manipulator involves a mechanical link system which has the same structure and scale as the slave robot-arm system. The forceps system is the same as the one that is used in the slave manipulator; likewise, it Is also located on the head of the link system (the reaction force is generated by the same motor-and-wire-driven system). A trocar system which can generate a reaction force against the movement of the master forceps was also designed and developed. In this system, force feedback was conducted by a "force reflection method". The position of the slave forceps was controlled in such a way as to mimic the movement of the master. The force which is generated when the slave manipulator touches or grips some object is detected by an increase in the electric current of the motors which drive the slave forceps; this current value is then used as a feedback factor in order to generate the reaction force against the movement of the master manipulator. The slave manipulator was found to accurately and quickly mimic the movement of the master manipulator, with the reaction force generated at the master manipulator also reproducing well the force that was actually applied to the slave manipulator.

Recently, there has been growing interest in sensory-motor integration for new behavior of intelligent robots. And the key component to this work is sensory information processing technology which is based on recent progress in the integration of electronic circuits, providing increased computing power at low cost. In this talk, a new type of vision chip which has a general purpose parallel processing array with photo detector in a single silicon chip will be discussed. The vision chip achieves 1 ms image processing, so mechanical systems can be controlled by using visual information with a 1 ms sampling rate. Additionally a 1 ms sensory motor fusion system, a new type of a hierarchical parallel sensory processing system, will be discussed. The system consists of integrated sensor modules and a parallel processing system providing for sensory feedback and novel performance. A demonstration of high speed grasping using visual and force feedback will be described.

A system was developed that supports virtually touching objects in a real environment by real-time transformation of visual data into haptic data. With the proposed system, local visual data of real objects are acquired using active vision the visual data are then subjected to high-speed parallel image processing, and transformed into virtual reactive forces from objects. A virtual tactile sensation is generated by exerting a reactive force on the operator's fingertip with a force display device. By using an original high-speed image processing system, the loop from visual data sensing through haptic display is operated at about 200 Hz. The present paper presents the basic concept of modality transformation, the system configuration, and results of experiments with objects of various shape carried out to verify the system's operation.

Recently, there are growing interests in applications of VLSI technology for sensory information processing based on the concept of "system on silicon". That means we can use fruitful computing power of compact VLSI at low cost. Therefore, the technology can open a new generation of intelligent systems. In this talk, a new type of vision chip which has general purpose parallel processing array with photo detector in a single silicon chip will be shown, The vision chip realize 1ms image processing, so mechanical systems can be controlled by using visual information with 1ms sampling rate. In addition, high speed grasping robot as a vision and force sensor fusion system will be shown, The system uses parallel DSP system for sensory feedback and novel performance can be implemented. A demonstration of the high speed grasping will be shown.