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Making robots capable of pouring can be useful in both service and industrial applications. Considering the importance of controlling liquid vibration in mixing chemical reagents and other industrial applications, we investigated in the this study robotic pouring with the aim of controlling liquid vibration, more specifically, the beer-foam ratio during beer pouring. We propose a vision-based measurement method that can measure the liquid volume with an error of less than 5% in real time. Besides, together with a proposed robot pouring controller, we develop a robot pouring system that can control ratio of beer-foam volume with an error of less than 5% during pouring. The flexibility of the developed system was also demonstrated through experiments using different types of container and beer. [ABSTRACT FROM AUTHOR]

Multiple-target tracking across multiple camera views is required for various practical tracking and surveillance applications. This study proposes a seamless tracking method based on label transfer using high-speed image capture. The proposed method does not require camera calibration to estimate the extrinsic parameters, and can be applied with simple line calibration. Therefore, it is effective for large-scale camera networks. In addition, owing to the features of the high-speed image capture and self-window, our method ensures seamless tracking of objects across multiple camera views. The feasibility of the method is proven through an experiment using a high-speed camera network system. [ABSTRACT FROM AUTHOR]

This study focuses on robotic assistance for peg-and-hole alignment with micrometer-order clearance. The objective of the robotic assistance is to cooperate with a human operator based on a coarse-to-fine strategy in which the human operator conducts coarse alignment and the robotic assistance realizes fine alignment. Robotic-assisted fine alignment is achieved by mimicking the process toward annularity of an annular solar eclipse. The first principal axis of a specified image feature (we call it a eclipse feature) is calculated by subtracting the surfaces of a hole part (a small gear with an inner diameter of 1 mm) and a peg part (a shaft with a diameter of 0.95 mm). Accordingly, control strategy is developed to realize accurate alignment. Moreover, the effectiveness of the proposed method is verified by experimental evaluation. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate the implementation of make-to-order bead art assembly without human intervention using dynamic compensation approach to achieve accurate real-time positioning and long-term adaptation for robotic automation in smart manufacturing. In the proposed framework, an industrial robot was designed to perform coarse global motion to implement low-bandwidth adaptation. Simultaneously, fine local motion to tackle real-time online uncertainties was achieved using an add-on robotic module to implement accurate positioning. The effectiveness of the proposed method was verified through experimental evaluations. [ABSTRACT FROM AUTHOR]

In multi-object tracking of identical objects, it is difficult to return to tracking after occlusions occur due to three-dimensional intersections between objects because the objects cannot be distinguished by their appearances. In this paper, we propose a method for multi-object tracking of identical objects using multiple high-speed vision systems. By using high-speed vision, we take advantage of the fact that tracking information, such as the position of each object in each camera and the presence or absence of occlusion, can be obtained with high time density. Furthermore, we perform multi-object tracking of identical objects by efficiently performing occlusion handling using geometric constraints satisfied by multiple high-speed vision systems; these can be used by appropriately positioning them with respect to the moving region of the object. Through experiments using table-tennis balls as identical objects, this study shows that stable multi-object tracking can be performed in real time, even when frequent occlusions occur. [ABSTRACT FROM AUTHOR]

Object tracking and pose estimation have always been challenging tasks in robotics, particularly for rotating objects. Rotating objects move quickly and with complex pose variations. In this study, we introduce a marker-based tracking and pose estimation method for rotating objects using a high-speed vision system. The method can obtain pose information at frequencies greater than 500 Hz, and can still estimate the pose when parts of the markers are lost during tracking. A robot catching experiment shows that the accuracy and frequency of this system are capable of high-speed tracking tasks. [ABSTRACT FROM AUTHOR]