Position recognition is one of the core technologies for driving a robot because of differences in environment and rapidly changing situations. This study proposes a strategy for estimating the position of a camera mounted on a mobile robot. The proposed strategy comprises three methods. The first is to directly acquire information (e.g., identification (ID), marker size and marker type) to recognize the position of the camera relative to the marker. The advantage of this marker system is that a combination of markers of different sizes or having different information may be used without having to update the internal parameters of the robot system even if the user frequently changes or adds to the marker’s identification information. In the second, two novel markers are proposed to consider the real environment in which real robots are applied: a nested marker and a hierarchical marker. These markers are proposed to improve the ability of the camera to recognize markers while the camera is moving on the mobile robot. The nested marker is effective for robots like drones, which land and take off vertically with respect to the ground. The hierarchical marker is suitable for robots that move horizontally with respect to the ground such as wheeled mobile robots. The third method is the calculation of the position of an added or moved marker based on a reference marker. This method automatically updates the positions of markers after considering the change in the driving area of the mobile robot. Finally, the proposed methods were validated through experiments.

This paper presents a static network equivalent model for Korean power systems. The proposed equivalent model preserves the overall transmission network characteristics focusing on power flows among areas in Korean power systems. For developing the model, a power transfer distribution factor (PTDF)-based k-means++ algorithm was used to cluster the bus groups in which similar PTDF characteristics were identified. For the reduction process, the bus groups were replaced by a single bus with a generator or load, and an equivalent transmission line was determined to maintain power flows in the original system model. Appropriate voltage levels were selected, and compensation for real power line losses was made for the correct representation. A Korean power system with more than 1600 buses was reduced to a 38-bus system with 13 generators, 25 loads, and 74 transmission lines. The effectiveness of the developed equivalent model was evaluated by performing power flow simulations and comparisons of various characteristics of the original and reduced systems. The simulation comparisons show that the developed equivalent model maintains inter-area power flows as close as possible to the original Korean power systems.

Various high-performance force/torque sensors have been developed for the purpose of advancing automation systems. However, the demand for simple torque measurement of rotating shafts continues to exist, and expensive multi-axis sensors need not be wasted here. In this paper we propose a simple motor-equipped single-axis reaction torque sensor to measure the applied torque continuously using a load cell. The proposed sensor has long lever and base linkages, and the adjustable moment arm consequently enables adjusting measurement range and sensitivity by repositioning the assembled load cell on the two linkages. This paper shows the design of the proposed torque sensor, and it is evaluated by experiments for various applied torque and lever length. Moreover, the sensor is applied to an existing example: a commercial balanced-arm lamp with and without its balancing spring. The proposed torque sensor can continuously and successfully measure the applied torque, and it will be utilized in various industries and laboratories without much money.

To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved.