It is difficult to automate the grasping of delicate fruits such as peaches, which require sensitive work. Envelope grasping is an effective approach for grasping such objects due to its large contact area with the object. A method to realize envelope grasping is the fingered gripper, which can perform grasping that follows the shape of the object through compliant interaction. However, this method has the problem that it is structurally difficult to fill the space between fingers. Another method of achieving enveloping grasp is to envelop the object by membrane. This method can touch the object without gap between fingers, but it is difficult to grasp unexpectedly large objects because it cannot deform as large as a fingered gripper. In this study, we propose a soft gripper that realizes envelope grasping while largely deforming several fingers. The proposed method opens and closes using the turning over of the hemispherical shell due to the 3D snap through buckling mechanism. By employing this mechanism, allowing all objects touching the edge of the hemispherical shell to be moved simultaneously and significantly, fingers arranged without gaps can be deformed largely. Another advantage is that it requires no energy to maintain the grasping state due to its bistable, snap through buckling characteristics. In this paper, we present a design methodology based on specific examples and an evaluation of performance.

This study develops a training system for a multimodal comprehensive care methodology for dementia patients called Humanitude. Humanitude has attracted much attention as a gentle and effective care technique. It consists of four main techniques, namely, eye contact, verbal communication, touch, and standing up, and more than 150 care elements. Learning Humanitude thus requires much time. To provide an effective training system for Humanitude, we develop a training system that realizes sensing and interaction simultaneously by combining a real entity and augmented reality technology. To imitate the interaction between a patient and a caregiver, we superimpose a three-dimensional CG model of a patient's face onto the head of a soft doll using augmented reality technology. Touch information such as position and force is sensed using the whole body wearable tactile sensor developed to quantify touch skills. This training system enables the evaluation of eye contact and touch skills simultaneously. We build a prototype of the proposed training system and evaluate the usefulness of the system in public lectures.

Detection of spatial change around a robot is indispensable in several robotic applications, such as search and rescue, security, and surveillance. The present paper proposes a fast spatial change detection technique for a mobile robot using an on-board RGB-D/stereo camera and a highly precise 3D map created by a 3D laser scanner. This technique first converts point clouds in a map and measured data to grid data (ND voxels) using normal distributions transform and classifies the ND voxels into three categories. The voxels in the map and the measured data are then compared according to the category and features of the ND voxels. Overlapping and voting techniques are also introduced in order to detect the spatial changes more robustly. We conducted experiments using a mobile robot equipped with real-time range sensors to confirm the performance of the proposed real-time localization and spatial change detection techniques in indoor and outdoor environments.

Technologies for machine automation are strongly demanded in some developed countries due to achieve various tasks which could not be treated by human. Autonomous Underwater Vehicles (AUVs) are currently being utilized for scientific, commercial and military applications. These vehicles require autonomous guidance and control systems in order to perform underwater tasks. Modeling, system identification and control strategy of these vehicles are still major areas of research and development. Various disturbance effects perturb a vehicle in underwater, but it is not really discussed by conventional control strategy. And thus this paper proposes a new control strategy which is still effective under the circumstances when the disturbance exists. Simulations were conducted for supporting the argument.

We aim to develop a supporting system which enhances the ability of human's short-term visual memory in an intelligent space where the human and a service robot coexist. Particularly, this paper focuses on how we can interpret and record diverse and complex life events on behalf of humans, from a multi-perspective viewpoint. We propose a novel method named "fourth-person captioning", which generates natural language descriptions by summarizing visual contexts complementarily from three types of cameras corresponding the first-, second-, and third-person viewpoint. We first extend the latest image captioning technique and design a new model to generate a sequence of words given the multiple images. Then we provide an effective training strategy that needs only annotations supervising images from a single viewpoint in a general caption dataset and unsupervised triplet instances in the intelligent space. As the three types of cameras, we select a wearable camera on the human, a robot-mounted camera, and an embedded camera, which can be defined as the first-, second-, and third-person viewpoint, respectively. We hope our work will accelerate a cross-modal interaction bridging the human's egocentric cognition and multi-perspective intelligence.

This paper proposes new software and hardware platforms named ROS-TMS and Big Sensor Box, respectively, for an informationally structured environment. We started the development of a management system for an informationally structured environment named Town Management System (TMS) in the Robot Town Project in 2005. Since then we have been continuing our efforts to improve performance and to enhance TMS functions. Recently, we launched a new version of TMS named ROS-TMS, which resolves some critical problems in TMS by adopting the Robot Operating System (ROS) and utilizing the high scalability and numerous resources of ROS. In this paper, we first discuss the structure of a software platform for the informationally structured environment and describe in detail our latest system, ROS-TMS version 4.0. Next, we introduce a hardware platform for the informationally structured environment named Big Sensor Box, in which a variety of sensors are embedded and service robots are operated according to the structured information under the management of ROS-TMS. Robot service experiments including a fetch-and-give task and autonomous control of a wheelchair robot are also conducted in Big Sensor Box.

This paper presents a near-future perception system named “Previewed Reality”. The system consists of an informationally structured environment (ISE), an immersive VR display, a stereo camera, an optical tracking system, and a dynamic simulator. In an ISE, a number of sensors are embedded, and information such as the position of furniture, objects, humans, and robots, is sensed and stored in a database. The position and orientation of the immersive VR display are also tracked by an optical tracking system. Therefore, we can forecast the next possible events using a dynamic simulator and synthesize virtual images of what users will see in the near future from their own viewpoint. The synthesized images, overlaid on a real scene by using augmented reality technology, are presented to the user. The proposed system can allow a human and a robot to coexist more safely by showing possible hazardous situations to the human intuitively in advance.

This paper proposes an actuation mechanism of robotic arms using rotational counterweights. The robotic arm is driven by gravitational and inertia forces of the counterweight mounted on links. The joints of the robotic arms are able to rotate freely though this robot does not have any actuators on joints. Thereby, the robot has high joint flexibility. Additionally, the counterweight system reduces the moment applied to base link caused by gravity effect since the posture of the arm keeps a gravitational equilibrium state statically. Therefore, it is expected that the robotic arm is utilized in narrow and high altitude environment or on small vehicles. This paper also proposes a control method of the new robotic arm. The control method realizes precise position control of joint angle. The usefulness of the method is demonstrated by numerical simulations and experiments using a prototype.

In recent years, several low-cost 3D laser scanners are being brought to the market and 3D laser scanning is becoming widely used in many fields. For example, 3D modeling of architectural structures or digital preservation of cultural heritages are typical applications for 3D laser scanning. Despite of the development of light-weight and high-speed laser scanners, however, the complicated measurement procedure and long measurement time are still a heavy burden for the widespread use of laser scanning. We have proposed a robotic 3D scanning system using multiple robots named CPS-SLAM, which consists of parent robots with a 3D laser scanner and child robots with target markers. In this system, a large-scale 3D model can be acquired by an on-board 3D laser scanner on a parent robot from several positions determined precisely by the localization technique using multiple robots named Cooperative Positioning System, CPS. Therefore, this system enables to build a 3D model without complicated post-processing procedures such as ICP. In addition, this system is an open-loop SLAM system and a quite precise 3D model can be obtained without closed loops. This paper proposes an automatic planning technique of a laser measurement for CPS-SLAM. By planning a proper scanning strategy depending on a target structure, it is possible to perform laser scanning efficiently and accurately even for a large-scale and complex environment. Proposed technique plans an efficient scanning strategy automatically by taking account of several criteria, such as visibility between robots, error accumulation, and efficient traveling. We conducted computer simulations and outdoor experiments to verify the performance of the proposed technique.

This paper presents an inflatable robotic arm controlled by a joystick to be used for healthcare applications. The arm is constructed almost entirely of plastic elements: inflatable links, air bag actuators, and acrylonitrile butadiene styrene (ABS) joints. Therefore, it is softer and lighter than typical robotic arms that are made of metal and heavy elements. Because the softness and lightness of the inflatable robotic arm is intrinsically safer, it is suitable for healthcare applications. In this paper, a new control method is proposed which allows the inflatable system to be controlled with a joystick. To verify the usefulness of the proposed method, we used an inflatable robotic arm with four degrees of freedom (4 DOF) to obtain experimental results for the control performance of the inflatable robotic arm. Moreover, we conducted preliminary tests which simulated patients controlling the robotic arm with a joystick in order to assist with eating their meals.

This paper focuses on a possibility of application of a method to simplification of robotic arm systems by removal joint encoders. The method which has been proposed achieves precise control of robotic arms using visual feedback with camera calibration errors. In this paper, the method is improved for an encoderless robotic arm system to ease several difficulties to use encoders. Encoders are fundamental components of most robotic arm systems to control joint angles precisely. However, encoders sometimes make some difficulties of wiring, structure and maintenance. The enhanced method for encoderless robotic arm systems is able to overcome these difficulties. Moreover, this method is also useful for robotic systems which have encoders since the method is able to be activated as a fail-safe system of robots with encoders just in case encoders are broken down. This new approach acquires information on joint angles from not encoders but estimation using back electromotive force. The information on joint angles includes some errors. The method, however, realizes precise manipulation. It is finally shown that this method allows errors caused by not only from camera calibrations but also joint angles.

This paper presents an improvement of our previously proposed dynamic object grasping and manipulation method. This method, which utilizes a dual-fingered hand of which each soft and hemispheric fingertip owns a torsional joint, has performed novel 3-dimensional dynamic object grasping and manipulation stably without the use of any external sensing device. However, several limitation and weakness have still remained in terms of dexterity and robustness. In order to improve it, firstly a triple-fingered hand is newly introduced instead of the dual-fingered hand to perform regrasping. Next, the previously proposed stable object grasping controller is adequately modified to perform dynamic regrasping during manipulation. Additionally, the virtual object attitude controller is also modified to improve its performance. Finally, several experiments are conducted by using a prototype, and the usefulness of proposed controller is demonstrated through these results.

This paper proposes a new visual servoing method for object manipulation robust to considerable time-delays of visual information. There still remain several problems in visual servoing methods although they are quite useful and effective for dexterous object manipulation. For instance, time-delays to obtain necessary information for object manipulation from visual images induce unstable behavior. The time-delays are mainly caused by low sampling rate of visual sensing system, computational cost for image processing, and latency of data transmission from visual sensor to processor. The method makes it possible to avoid such unstable behavior of the systems due to considerable time-delays using virtual object frame defined by only each joint angle. Firstly, a new control scheme for object manipulation using the virtual object frame is designed. Next, numerical simulations are conducted to verify the effectiveness of the control scheme. Finally, experimental results are shown to demonstrate the practical usefulness of proposed method.

This paper proposes a novel vision-based grasping and manipulation scheme of a multi-fingered hand-arm system robust for a temporary lack of sensory information. Visual information is one of the fundamental components for reliable grasping and manipulation by a multi-fingered hand-arm system. However, in case that visual information such as position and attitude of an object comes to be unavailable due to the occlusion or if the object goes out-of-sight temporarily, unstable and unfavorable behavior is often induced. The proposed method, which utilizes the stable grasping control and the concept of virtual frame, enables to grasp and manipulate an object stably even if the visual information becomes suddenly and temporarily unavailable during manipulation. Firstly, a dynamical model of object grasping using a multi-fingered hand-arm system is formulated. Next, a new control scheme for robust object grasping and manipulation using the virtual frame is proposed. Finally, numerical simulations are performed to verify the usefulness of the proposed method.

This paper proposes a novel control method for stable grasping using a multi-fingered hand-arm system with soft hemispherical finger tips. The proposed method is simple but easily achieves stable grasping of an arbitrary polyhedral object using an arbitrary number of fingers. Firstly, we formulate nonholonomic constraints between a multi-fingered hand-arm system and an object constrained by rolling contact with finger tips, and derive a condition for stable grasping by stability analysis. A new index for evaluating the possibility of stable grasping is proposed and efficient initial relative positions between finger tips and the object for realizing stable grasping are analyzed. The stability of the proposed system and the validity of the index are verified through numerical simulations.