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Object detection and tracking in camera images is a fundamental technology for computer vision and is used in various applications. In particular, object tracking using high-speed cameras is expected to be applied to real-time control in robotics. Therefore, it is required to increase tracking speed and detection accuracy. Currently, however, it is difficult to achieve both of those things simultaneously. In this paper, we propose a tracking method that combines multiple methods: correlation filter-based object tracking, deep learning-based object detection, and motion detection with background subtraction. The algorithms work in parallel and assist each other's processing to improve the overall performance of the system. We named it the "Mutual Assist tracker of feature Filters and Detectors (MAFiD method)". This method aims to achieve both high-speed tracking of moving objects and high detection accuracy. Experiments were conducted to verify the detection performance and processing speed by tracking a transparent capsule moving at high speed. The results show that the tracking speed was 618 frames per second (FPS) and the accuracy was 86% for Intersection over Union (IoU). The detection latency was 3.48 ms. These experimental scores are higher than those of conventional methods, indicating that the MAFiD method achieved fast object tracking while maintaining high detection performance. This proposal will contribute to the improvement of object-tracking technology. [ABSTRACT FROM AUTHOR]

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]

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]

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]

This paper focuses on development of a high-speed, low-latency telemanipulated robot hand system, evaluation of the system, and demonstration of the system. The characteristics of the developed system are the followings: non-contact, high-speed 3D visual sensing of the human hand, intuitive motion mapping between human hands and robot hands, and low-latency, fast responsiveness to human hand motion. Such a high-speed, low-latency telemanipulated robot hand system can be considered to be more effective from the viewpoint of usability. The developed system consists of a high-speed vision system, a high-speed robot hand, and a real-time controller. For the developed system, we propose new methods of 3D sensing, mapping between the human hand and the robot hand, and the robot hand control. We evaluated the performance (latency and responsiveness) of the developed system. As a result, the latency of the developed system is so small that humans cannot recognize the latency. In addition, we conducted experiments of opening/closing motion, object grasping, and moving object grasping as demonstrations. Finally, we confirmed the validity and effectiveness of the developed system and proposed method. [ABSTRACT FROM AUTHOR]

In this research, we focused on Human-Robot collaboration. There were two goals: (1) to develop and evaluate a real-time Human-Robot collaborative system, and (2) to achieve concrete tasks such as collaborative peg-in-hole using the developed system. We proposed an algorithm for visual sensing and robot hand control to perform collaborative motion, and we analyzed the stability of the collaborative system and a so-called collaborative error caused by image processing and latency. We achieved collaborative motion using this developed system and evaluated the collaborative error on the basis of the analysis results. Moreover, we aimed to realize a collaborative peg-in-hole task that required a system with high speed and high accuracy. To achieve this goal, we analyzed the conditions required for performing the collaborative peg-in-hole task from the viewpoints of geometric, force and posture conditions. Finally, in this work, we show the experimental results and data of the collaborative peg-in-hole task, and we examine the effectiveness of our collaborative system. [ABSTRACT FROM AUTHOR]

In this paper, we develop a new sensor network system with a high sampling rate (over 500 Hz) based on the simultaneous synchronization of clock and data acquisition for integrating the data obtained from various sensors. Hence, we also propose a method for the synchronization of clock and data acquisition in the sensor network system. In the proposed scheme, multiple sensor nodes including PCs are connected via Ethernet for data communication and for clock synchronization. The timing of the data acquisition of each sensor is locally controlled based on the PC’s clock locally provided in the node, and the clocks are globally synchronized over the network. We construct three types of high-speed sensor network systems using the proposed method: the first one is composed of a high-speed tactile sensor node and a high-speed vision node; the second one is composed of a high-speed tactile sensor node and three acceleration sensor nodes; and the last one is composed of a high-speed tactile sensor node, two acceleration sensor nodes, and a gyro sensor node. Through experiments, we verify that the timing error between the sensor nodes for data acquisition is less than 15 μs, which is significantly smaller than the time interval of 2 ms or a shorter sampling time (less than 2 ms). We also confirm the effectiveness of the proposed method and it is expected that the system can be applied to various applications. [ABSTRACT FROM AUTHOR]