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Öğe The Effect of Rotor Plates on Capacitive Measurement in Capacitive Encoders(IEEE, 2020) Yavsan, Emrehan; Karali, Mehmet; Gokce, Baris; Erismis, Mehmet AkifThe moving plates of the capacitive encoders are called rotors and the fixed plates are called stators. In this study, the effects of the rotor plates on capacitive measurement for capacitive encoders are analyzed. Encoders are used in angular position measurement. They can be preferred especially in most applications where rotational motion occurs in the robotic application areas. The application areas of the encoders can be further extended with the capacitive encoder technology. The capacitive encoder technology is based on measuring the capacitances between the encoder plates. As the capacitances vary depending on the overlapping areas of the encoder plates, the shapes and the patterns of the encoder plates directly affect the capacitive measurement. Therefore, the capacitive encoder plate selections must be made correctly. There are very few studies on the selection of the capacitive encoder plates. It is seen that the current studies generally continue on a similar type rotor patterns. Various rotor plates are proposed in this study for the capacitive encoder that we are in the development process. After the rotor patterns are expressed mathematically and the capacitive encoders using rotors with these patterns are compared. The comparison process was made by calculating the equivalent capacitance between the proposed capacitive encoder plates. The effects of rotors with different materials and patterns on the capacitive measurement were investigated. Thus, a contribution was made to the effective development of similar capacitive sensors.Öğe Gesture imitation and recognition using Kinect sensor and extreme learning machines(Elsevier Sci Ltd, 2016) Yavsan, Emrehan; Ucar, AysegulThis study presents a framework that recognizes and imitates human upper-body motions in real time. The framework consists of two parts. In the first part, a transformation algorithm is applied to 3D human motion data captured by a Kinect. The data are then converted into the robot's joint angles by the algorithm. The human upper-body motions are successfully imitated by the NAO humanoid robot in real time. In the second part, the human action recognition algorithm is implemented for upper-body gestures. A human action dataset is also created for the upper-body movements. Each action is performed 10 times by twenty-four users. The collected joint angles are divided into six action classes. Extreme Learning Machines (ELMs) are used to classify the human actions. Additionally, the Feed-Forward Neural Networks (FNNs) and K-Nearest Neighbor (K-NN) classifiers are used for comparison. According to the comparative results, ELMs produce a good human action recognition performance. (C) 2016 Elsevier Ltd. All rights reserved.Öğe A New Discrete Analog Circuit Solution for Capacitive Rotary Encoders(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Kara, Muhammet Rojhat; Yavsan, Emrehan; Karali, Mehmet; Erismis, Mehmet AkifIn the time of global chip crisis, it is clear that alternative electronic solutions are necessary; particularly for capacitive rotary encoders, or similar capacitive sensors where demodulation techniques are extensively used. In this work, a discrete analog switch based circuit solution is proposed for the capacitive rotary encoders for the first time in the literature to the best of our knowledge. A 3-layer uniquely designed capacitive encoder prototype is used as a capacitive sensor. The analog switch with OPAMP based demodulation configuration designed for this work is both cheaper and it works at higher frequencies than the analog multiplier configuration. Also, unlike ASIC, it does not require high-tech for production. With the established test setup; noise, smallest perceptible capacitance, nonlinearity and temperature analyses of the circuit were made and competing resultswere achieved. The noise levels in terms of degree and voltage are measured as 0.0063 degrees and 36.62 mu V root Hz; respectively. Minimum measurable capacitance achieved with the discrete analog circuit is 2.54 aF root Hz. Nonlinearity was found to be 0.29% which is highly correlated with the mechanical misalignments of the capacitive encoder. Although this particular study is carried out on capacitive encoders, the proposed circuit solution can be used for similar types of sensors.Öğe A novel high resolution miniaturized capacitive rotary encoder(Elsevier Science Sa, 2021) Yavsan, Emrehan; Kara, Muhammet Rojhat; Karali, Mehmet; Gokce, Baris; Erismis, Mehmet AkifIn this paper, design and prototyping of a novel, high resolution, and low-cost capacitive encoder were presented. Detailed analysis showed that the number of poles on the rotor should be as high as possible to keep the gain high and to reduce the non-linearity. Moreover, contrary to the common intuition, inter electrode gap is found to have an optimum non-zero value, corresponding to a particular number of poles, in order to maximize the gain. However, increasing number of poles brings practical problems due to manufacturing limits and digital electronic frequency load. As the electronics, micro-controller based digital signal processing is used to keep the cost as low as possible. With miniaturizing the encoder geometry as a design target, the number of plates were increased to three to increase the capacitances. One prototype, which is around 3 cm in diameter could be successfully mounted to an industry oriented DC motor and tested. The tests of this miniaturized encoder showed non-linearity error of 0.12% and resolution of 0.02 degrees. One source of the non-linearity error is the DC motor itself, and we believe that with a better setup, the error could be measured to be even better. (C) 2021 Elsevier B.V. All rights reserved.Öğe Teaching Human Gestures to Humanoid Robots by Using Kinect Sensor(IEEE, 2015) Yavsan, Emrehan; Ucar, AysegulIn this study, a novel algorithm is developed to recognize human actions and reproduce human actions on a humanoid robot. The study consists of two parts. In the first part, the real time human imitation system is realized. The three dimensional skeleton joint positions obtained from Xbox 360 Kinect. These positions are transformed to joint angles of robot arms via a transformation algorithm and these angles are transferred to NAO robot. The human upper body movements are finally successfully imitated by NAO robot in real time. In the second part, the algorithm is generated for the recognition of human actions. Extreme Learning Machines (ELMs) and the Feed Forward Neural Networks (FNNs) with back propagation algorithm are used to classify actions. According to the comparative results, ELMs produce a better recognition performance.
