Smoothness is one of the important factors in controlling texture sensation in tactile VR. In previous research, the authors utilized Velvet Hand Illusion (VHI), which is a tactile illusion phenomena, to generate a smooth texture on a dot-matrix display. Since the dot-matrix display can generate arbitrary figures, we are attempting to evaluate our new hypothesis of the VHI mechanism using this display. In our hypothesis, a cognitive mechanism called Gestalt grouping [3] is related to VHI occurrence. If tactile Gestalt were elucidated, we could understand the tactile sensation mechanism deeply and the various devices would be developed in the VR research field. In this paper, we investigate the relationship between tactile Gestalt and VHI through psychophysical experiments. In these experiments, the appearance intensity of tactile Gestalt is controlled by means of density and length of the lines formed on the dot-matrix display. It is concluded that the law of closure stated in the principle of Prägnanz is an essential condition related to tactile Gestalt to generate VHI.

Three-axis tactile sensing has advantages for grasping an object of unknown mass and hardness. We developed a new three-axis tactile sensor that possesses a simple structure to endure a large applied force from a powerful grasp. Normal force distribution is measured based on grayscale values obtained by image data processing, as with previous three-axis tactile sensors. Tangential force distribution is determined by the linear movement of image data calculated by optical flow. The sensing characteristics of this sensor are dominated by the configuration and material of fine conical feelers formed on a silicon rubber sheet. By UV-LIGA, we obtain a fine mold of a silicon rubber sheet. In evaluation experiments, we applied both normal and tangential force to the sensor and confirmed this tactile sensor's ability to acquire normal and tangential forces. In its design, we utilize a USB microscope that has a CMOS camera and a light source. In a series of experiments, we performed normal and tangential force tests to obtain its basic characteristics. The linear relationship between the grayscale value and the normal force is obtained from the normal force test. If the average optical flow is under 0.2 mm, the tangential force is proportional to the average optical flow. The slope of the relationship between the tangential force and the average optical flow increases with additional normal force. Finally, we derive a series of equations for three-axis force calculation.

In a previous paper, we developed a robotic finger equipped with optical three-axis tactile sensors, of which the sensing cell can separately detect normal and shearing forces. With appropriate precision, the robotic finger was able to perform three tasks: scanning flat specimens to obtain the friction coefficient, following the contour of objects, and manipulating a parallelepiped case put on a table by sliding it on the table. In the present study, designed as a follow-up to the above study, a robotic hand is composed of two robotic fingers. Not only tri-axial force distribution directly obtained from the tactile sensor but also the time derivative of the shearing force distribution are used for the hand control algorithm: if grasping force measured from normal force distribution is lower than a threshold, grasping force is increased; the time derivative is defined as slippage; if slippage arises, grasping force is enhanced to prevent fatal slippage between the finger and an object. In the verification test, the robotic hand screws a bottle cap to close it. Although input finger trajectories were a rectangular roughly decided to touch and screw the cap, a segment of the rectangular was changed from a straight line to a curved line to fit the cap contour. We concluded that higher order tactile information such as tri-axial tactile data can reduce the complexity of the control algorithm.

This paper presents a new algorithm for object handling tasks based on active tactile and slippage sensations using a humanoid robot multifingered arm for an object that exists at an arbitrary position. The idea is to enhance real-time object handling tasks based on tactile sensing in humanoid robotics, where grasp, move and release motions are involved. We developed a novel hemisphere-shaped optical three-axis tactile sensor to mount on fingertips of the robot arm. The tactile sensor is capable of defining normal and shearing forces simultaneously. For grasp and release motions, we designed the algorithm based on slippage direction analysis consisting of coordinate transformation of the sensing element for the arm global coordinate. The robot control system uses the analysis results to determine whether an object is in contact with the ground without needing to measure the height of the ground. The algorithm was evaluated in experiments with soft and hard objects, whereby results revealed good performance for the robot fingers in handling an object at an arbitrary position.

This paper present object handling capabilities of two robotic hands equipped with optical three-axis tactile sensor. We present optimization of grasp control in tactile sensor and robot hand control system to precisely control robot hand based on tactile sensing information. To enhance performance of the robot hand, stiffness distinction parameters were applied in the control system. These parameters are used to select velocity ratio of robot hand to control re-push motion and define optimum grasp pressure. In addition, slippage recognition method is also applied so that the robot hand can grasp and handle object located at arbitrary position. The proposed control system and parameters were evaluated in object handling experiments with hard and soft objects, and object located at arbitrary position. Experimental results revealed good performance for the robot hand in handling hard and soft objects, and object located at an arbitrary position.

In a previous paper we developed an optical three-axis tactile sensor that can acquire normal and shearing forces to be mounted on a robotic finger. Normal and shearing forces applied to the sensing element were detected separately; when we examined the repeatability of the present tactile sensor with 1,000 loading-unloading cycles, the respective error of the normal forces was 2%. In the present paper, the three-axis tactile sensor is mounted on a robotic finger of three degrees of freedom to evaluate it for dexterous hands. A series of three kinds of experiments were performed. First, the robotic hand touches and scans flat specimens to evaluate the sensing ability of the friction coefficient. Second, it detects the contour of parallelepiped and cylindrical objects. Finally, it manipulates a parallelepiped case put on a table by sliding it on the table. Since the present robotic hand was able to perform the above three tasks with appropriate precision, we expected that it would be applicable to dexterous hands in subsequent studies.

This paper presents an application of a low force interaction method in a control scheme of robot manipulation based on tactile sensing. Our aim is to develop an intelligent control system that can distinguish the hardness of unknown objects so that robotic fingers can effectively explore the object’s surface without altering its physical properties or causing damage. Initially we developed a novel optical three-axis tactile sensor system based on an optical waveguide transduction method capable of acquiring normal and shearing forces. The sensors are mounted on the fingertips of the multi-fingered humanoid robot arm. We proposed a new control scheme applying low force interaction to distinguish the hardness of unknown objects in robot manipulation tasks based on tactile sensing. The scheme utilized new control parameters obtained by calibration experiments using hard and soft objects that enable robot fingers to precisely control grasp pressure and define the slippage sensation of the given object. Finally, verification experiments of the proposed control scheme using a humanoid robot arm were conducted whose results revealed that the finger’s system managed to recognize the hardness of unknown objects and complied with sudden changes of the object’s weight during object manipulation tasks.

This paper presents development of tactile sensing-based control algorithm for humanoid robot finger system with optical three-axis tactile sensor mounted on fingertips. Our aim is to develop an intelligent control system that can recognize stiffness of unknown objects and respond to sudden changes of object’s weight during object manipulation. For this purpose, we developed a novel optical three-axis tactile sensor system based on an optical waveguide transduction method capable of acquiring normal and shearing forces. We proposed a control algorithm in the finger control system based on tactile and slippage sensations, and analyzed real-time grasp synthesis in object manipulation tasks. The control algorithm was designed to control fingertips movements by defining optimum grasp pressure and perform re-push movement when slippage was detected in object manipulation tasks. Verification experiments using humanoid robot fingers were conducted whose results revealed that the finger’s system managed to recognize the stiffness of unknown objects and complied with sudden changes of the object’s weight during object manipulation tasks.

This paper presents the development of a contact interaction-based navigation strategy for a biped humanoid robot with the aim of supporting current visual-based navigation. The robot arms are equipped with force sensors to detect physical contact with objects. We proposed a motion algorithm consisting of searching tasks, self-localization, correction of locomotion direction and obstacle avoidance. Priority is given to right-side direction to navigate the robot locomotion in conjunction with a strategy to avoid obstacles. The proposed algorithm is evaluated in an experiment with a humanoid robot operating in a room with walls and obstacles. The experimental results reveal good performance of the robot when recognizing objects by touching and grasping, continuously generating suitable trajectory to correct locomotion direction and avoiding collisions.

This paper presents the application of a six-axis force sensor and a novel optical three-axis tactile sensor to humanoid robot navigation system which is based on contact interaction towards supporting visual-based navigation. The force sensors are mounted on humanoid robot arms to perform grasping in self-localization task to define the robot's position and orientation. The grasping results guided the robot locomotion and avoid it from collision. Meanwhile the optical three-axis tactile sensors are mounted on cooperative two-finger system for object handling tasks. The tactile sensor is capable of acquiring normal force and shearing force. Experiment with hard and soft objects are performed which results revealed good performance of the integrated robotic fingers and tactile sensor system to recognize and grip the objects. The presented control algorithms for both sensors are capable of preventing the probability of damage to the sensors and objects during robust grasping and object handling tasks.

We are developing an optical three-axis tactile sensor capable of acquiring normal and shearing force, with the aim of mounting it on a robotic finger. The tactile sensor is based on the principle of an optical waveguide-type tactile sensor, which is composed of an acrylic hemispherical dome, a light source, an array of rubber sensing elements, and a CCD camera. The sensing element of silicone rubber comprises one columnar feeler and eight conical feelers. The contact areas of the conical feelers, which maintain contact with the acrylic dome, detect the three-axis force applied to the tip of the sensing element. Normal and shearing forces are then calculated from integration and centroid displacement of the gray-scale value derived from the conical feeler's contacts. To evaluate the present tactile sensor, we have conducted a series of experiments using a y-z stage, a rotational stage, and a force gauge, and have found that although the relationship between the integrated gray-scale value and normal force depends on the sensor's latitude on the hemispherical surface, it is easy to modify the sensitivity according to the latitude, and that the centroid displacement of the gray-scale value is proportional to the shearing force. When we examined repeatability of the present tactile sensor with 1,000 load-unload cycles, the respective error of the normal and shearing forces was 2 and 5%

This paper presents a design of a 21-DOF humanoid robot from the perspective of DOFs and joint angle range characteristic to identify elements that provide flexibility to attain human-like motion. Description and correlation of physical structure flexibility between human and humanoid robot to perform motion is presented to clarify the elements. The investigation is focusing in joint structure design, configuration of DOF and joint rotation range of 21-DOF humanoid robot Bonten-Maru II. Experiments utilizing this robot were conducted, with results indicates effective elements to attain flexibility in human-like motion

To develop a new three-axis tactile sensor for mounting on multi-fingered robotic hands, in this work we optimize sensing elements on the basis of our previous works concerning optical three-axis tactile sensors with a flat sensing surface. The present tactile sensor is based on the principle of an optical waveguide-type tactile sensor, which is composed of an acrylic hemispherical dome, a light source, an array of rubber sensing elements, and a CCD camera. The sensing element of the present tactile sensor comprises one columnar feeler and eight conical feelers. The contact areas of the conical feelers, which maintain contact with the acrylic dome, detect the three-axis force applied to the tip of the sensing element. Normal and shearing forces are then calculated from integration and centroid displacement of the gray-scale value derived from the conical feeler's contacts. To evaluate the present tactile sensor, we have conducted a series of experiments using a y-z stage, a rotational stage and a force gauge, and have found that although the relationship between integrated gray-scale value and normal force depends on the latitude on the hemispherical surface, it is easy to modify the sensitivity according to the latitude, and that the centroid displacement of the gray-scale value is proportional to the shearing force. Finally, to verify the present tactile sensor, we performed a series of scanning tests using a robotic manipulator equipped with the present tactile sensor to have the manipulator scan surfaces of fine abrasive papers. Results show that the obtained shearing force increased with an increase in the particle diameter of aluminium dioxide contained in the abrasive paper, and decreased with an increase in the scanning velocity of the manipulator over the abrasive paper. Because these results are consistent with tribology, we conclude that the present tactile sensor has sufficient dynamic sensing capability to detect normal and shearing forces.

This paper describes a new three-axis tactile sensor equipped with an optical waveguide plate mounted on a robot manipulator. After a series of FEM contact analyses and evaluation experiments were conducted, an experimental large-sized tactile sensor intended for employment in evaluation experiments was designed and produced. The experimental results confirmed that the tactile sensor is capable of detecting the distribution of three-axis force and that the calculated and experimental results coincide well. On the basis of these results, a smaller tactile sensor mounted on a robot manipulator was designed and produced. This tactile sensor comprises a CCD camera, a light source, an acrylic board and a silicon rubber sheet that are assembled into a casing 180 mm long, 80 mm wide and 50 mm thick.