Task completion time and cost are two significant criteria for the selection of manipulator system. For a given task, several Pareto solutions of manipulator systems should be derived based on the evaluation of these two criteria. However, this process requires a large calculation time. In this paper, we propose a method that can select appropriate systems by evaluating task completion time and cost within the desired calculation time. In the proposed method, multiple objective particle swarm optimization (MOPSO) is employed to search for appropriate manipulator systems from a set of candidate systems. Location optimization and motion coordination are integrated to derive the task completion time and the relative cost is used to evaluate the cost of a manipulator system. We employ particle swarm optimization (PSO) for location optimization and use nearest-neighborhood algorithm (NNA) for motion coordination, since PSO and NNA have a high speed of convergence to a good solution. The proposed method is applied to a set of tasks and is proved to be effective and practical.

Long-time exposure to repetitive or monotonous work is associated with increased risk for musculoskeletal disorders that are due to muscle fatigue. Previously, researchers reported that muscle fatigue can be estimated using a low-frequency band of an SEMG signal. However, these studies were performed exclusively during static contraction tasks. The objective of the present study was to evaluate and determine the frequency range for a low-frequency band. In addition, the performance during dynamic contraction tasks was analyzed. A group of healthy university students (8 males) was recruited, and endurance handgrip tasks were conducted. SEMG signals were captured from the forearm muscle. The frequency range for the low-frequency band was redefined as 5 - 40 Hz. The results from a dynamic contraction task indicated that a low-frequency band is a reliable method for indexing muscle fatigue from SEMG signals.

We have proposed “attentive workbench (AWB),” an assembly cell that supports the production activities of human workers. Attentive Workbench is composed of an augmented desk interface and self-moving trays with the Sawyer planar motors. In this paper, real assembly experiments using the implemented AWB system are carried out. The merit of the physical assembly support by the proposed system is evaluated quantitatively in the view of necessary time for product assembly.

We aim to realize an intelligent robotic system that delivers necessary objects to human desk-workers in home or office environments. In order to meet this goal, we propose methods to understand a request for support of a user of the system. We adopt an approach that the system measures the userpsilas hand and eye movements in reaching for an object to detect and understand the request. Based on the detection and understanding of the request, the system delivers necessary objects to the user using self-moving trays. The experimental results demonstrate the advantage of the methods proposed here.

We aim to realize a robotic system that hands over a necessary object to a user as soon as he/she attempts to reach out his/her hand for it. In order to realize such system, the following is required: 1) detection of the reaching movements, 2) prediction of the target object among multiple objects, and 3) handing-over the object to a user. In this paper, the first two of them are discussed. To detect the reaching movements, we use the speed of a hand movement, the smoothness of the hand trajectory, and the relation between a position of hand and a gaze point. To predict the target object, we use a probabilistic model based on the user's hand movements and his/her gaze direction. The proposed system can detect reaching movements and predict the target object at a very early stage. A description of the experimental results demonstrates the advantage of the method proposed here.

Semiconductor manufacturing is mainly characterized by diversity of products, different process types, and random failures. It is extremely difficult to solve scheduling problems due to high frequency of disturbance occurrence. This paper proposes a new approach for the online manufacturing rescheduling method. Instead of having a dispatching process based on dispatching rules once again, we revise the existing schedule based on message passing principle once the disturbance occurs, and improve the performance of the revised schedule by the introduction of a quick local search according to permutations of processes on semi-critical paths. The proposed method can release the influence of disturbances in less than 1 second, and finish rescheduling process in less than 1 minute. Through the actual problems with about 200,000 processes, this method is evaluated to be more effective for actual manufacturing than the dispatching-rule based methods, some of which have been applied in many facilities

We have proposed "attentive workbench (AWB)," a deskwork support system. Using cameras, projectors, and self-moving trays, the system supports human user from both physical and informational aspects. In this paper, an interface between the user and AWB based on pointing gestures is developed. Considering the usage of AWB, a simple and reliable interface with quick response is implemented. Deskwork support using the present interface and real self-moving trays are demonstrated

We aim to realize a robotic system that hands over a necessary object to a user as soon as he/she attempts to reach out for it. In order to realize such system, the following is required: 1) detection of the reaching movement, 2) prediction of the target object among multiple objects, and 3) handing over the object to a user. In this paper, the first two of them are described and discussed. We apply the smoothness and the speed of the hand movement to distinguish whether the movement is for reaching or not. And in order to predict the target object, we define the certainty according to the relative movement of the hand to each object. To evaluate the performance of the proposed method, we compare the method with the minimum jerk model based approach. A description of the experimental results demonstrates the usefulness of the method proposed here

We propose “Attentive Workbench (AWB),” a new cell production system in which an intelligent system supports human workers. Using cameras, projectors, planar motor driven self-moving trays and other devices, the system supports workers from both physical and information aspects, recognizing worker’s condition and intention. This paper outlines AWB and deals with physical assembly support using self-moving parts trays. Two different schemes, centralized and decentralized, for controlling multiple parts trays are evaluated through experiments and simulations. The centralized control scheme is found to have the higher performance than the decentralized control scheme.

The job-shop scheduling problem (JSSP) is one of the most difficult NP-hard combinatorial optimization problems. It is extremely difficult to solve the complex job shop scheduling problems because of the disturbances of manufacturing environment. This paper proposes a new method based on the reaction-diffusion equation on a graph [Yuasa, H and Ito, M (1998)] to solve JSSP with disturbances. This method considers the operations of JSSP as the autonomous decentralized system elements. According to the definition of the local potential functions between two operations (two operations on the same machine or the same job), the original schedule can be revised to accommodate with the disturbances of manufacturing, such as machine breakdown, processing time variation, in a short time. The present method is tested for benchmark problems with disturbances.

We have proposed "attentive workbench (AWB)", a new cell production system in which an intelligent system supports human workers. Recognizing worker's condition and intention, the system supports workers from both physical and information aspects. This paper deals with physical assembly support using self-moving parts trays. The system delivers necessary assembly parts to workers and clears finished products quickly. On transporting large products, multiple trays are subjected to form a rigid body working as a large single tray. In order to realize this arrangement of trays in real-time, a planning method based on the priority scheme and heuristic rule is proposed. The present method is evaluated through simulations. A demonstration of assembly support using real self-moving trays is shown.

We have proposed "attentive workbench (AWB)," a deskwork support system. Using cameras, projectors, and self-moving trays, the system supports human from both physical and informational aspects. This paper deals with the problem for estimating the object that a user needs. We present one of the approaches for accurate estimation of a necessary object from the user's pointing gesture. The system arranges the self-moving trays by itself based on the user's past action sequences. Using force-directed method, good placement, which decrease false estimations and is not moved very much from the initial placement, can be obtained. A description of the experimental results demonstrates the usefulness of the method proposed here.

In this paper, a flexible robotic assembly system with decentralized architecture is presented. The system is designed to achieve high reconfigurability so that it can adapt to changes in manufacturing environment; a new robot can be easily installed to the system and execute assembly tasks immediately, together with other devices. For easier reconfiguration, a semi-automated calibration method for positions of newly installed robots is integrated into the system. Our implementation of the assembly system consists of conventional manipulators and a belt conveyor. In the experiment, a new mobile manipulator was installed successfully and performed an assembly operation jointly with other existing manipulators.

Proposes a flexible assembly system, where autonomous manufacturing devices and production management agents communicate with one another to accomplish production tasks. This architecture allows the system to arrange manufacturing devices independently of the type of products assembled and to assemble multiple products in parallel and asynchronous progress. This system also supports plug and produce, a system function that realizes easy reconfiguration. Thus, the system can return quick responses to breakdowns and changes in production quantities. This paper also presents an index for the general evaluation of reconfigurable manufacturing systems. With this index and the plug-and-produce function, the system can be reconfigured appropriately to adapt to changes in the manufacturing environments.

This paper proposes a flexible assembly system that manages production by negotiating with autonomous manufacturing devices. With this mechanism, physical layout of the system is independent of the type of products to be assembled, and the system can asynchronously process multiple parallel production tasks. This system also supports plug and produce: a system function that enables easy reconfiguration. Thus, the system can be quickly accommodated to breakdowns and changes in production quantities. This paper also deals with an index for general evaluation of the manufacturing systems. With this index, we can plan appropriate improvement of the system layouts. Then we reconfigure the system using plug and produce function, in order to accommodate it to the changes in the manufacturing environments.