Kybernetika a robotika
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- ItemOn a class of difference equations with interlacing indices(Springer, 2021-06-16) Stevič, Stevo; El-Sayed, Ahmed; Kosmala, Witold; Šmarda, ZdeněkSome results on the long-term behavior of solutions to a class of difference equations,which includes numerous nonlinear difference equations of various orders thatattracted some attention in the last 15 years, are presented. We also present a naturalconnection among these difference equations, compare some results on theequations with some other ones in the literature, and give a list of a considerablenumber of difference equations which can be treated in a similar way
- ItemParameter Estimation and Control Structure Synthesis for Oscillatory Mechanical Two-Mass Systems(IEEE, 2024-06-07) Bartík, OndřejThis work presents a complete procedure of the closed-loop control system tunning for the electric drive with a two-mass flexible actuator. The Welch method and frequency analysis are used for the plant’s parameter identification. The feedback compensator based on the time derivative of the acceleration is designed to compensate for the plant oscillations. Model reference control (MRC) control law is used for the velocity control design. An additional actuator end-point model-based observer is designed. The whole proposed methodology is tested and demonstrated on the experimental test bench. The results are discussed and compared with the existing methods.
- ItemImprovement of the Temperature Stability of the Erbium-Doped Superfluorescent Fiber Source by Tuning the Reflectivity of the Fiber End(IEEE, 2023-03-15) Skalský, Michal; Hnidka, Jakub; Havránek, ZdeněkA novel and simple way of improving the mean wavelength temperature stability of the erbium-doped superfluorescent source is described and demonstrated. We show that by introducing small reflectivity feedback at the unpumped fiber end in the backward-pump superfluorescent source configuration, we can affect an overall temperature dependency of the mean wavelength of the output spectrum. The reflectivity adjustment can be made by an angled fiber cleave, varying the reflectivity between 0 to 4 %, or by a fusion arc, allowing its finer adjustment. With this approach, we were able to arbitrarily adjust the mean wavelength temperature trend from -4.38 to 5.23 ppm/ C. Furthermore, an optimal reflectivity was attained, providing almost zero trend and reducing the total mean wavelength variation to 130 ppm over the temperature range of -40 to +100 C, which is a 5.7-fold and 4.4-fold improvement compared to 0 and a standard 8 fiber cleave angle, respectively. By avoiding any filtering components, a wide bandwidth of 37.8 nm and a power efficiency of 22% was reached. Since the proposed configuration does not include any extra components compared to the basic backward-pump configuration, it can be a viable solution for cost-efficient applications, such as, e.g., medium-grade fiber-optic gyroscopes. A benefit for these gyroscopes is the tunability of the source wavelength temperature dependency which can conveniently compensate the gyro coil temperature sensitivity.
- ItemBrno Urban Dataset: Winter Extension(Elsevier, 2022-01-01) Ligocki, Adam; Jelínek, Aleš; Žalud, LuděkThis paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (WE). The dataset contains data from commonly used sensors in the automotive industry, like four RGB and single IR cameras, three 3D LiDARs, differential RTK GNSS receiver with heading estimation, the IMU and FMCW radar. Data from all sensors are precisely timestamped for future offline interpretation and data fusion. The most significant gain of the dataset is the focus on the winter conditions in snow-covered environments. Only a few public datasets deal with these kinds of conditions. We recorded the dataset during February 2021 in Brno, Czechia, when fresh snow covers the entire city and the surrounding countryside. The dataset contains situations from the city center, suburbs, highways as well as the countryside. Overall, the new extension adds three hours of real-life traffic situations from the mid-size city to the existing 10 h of original records. Additionally, we provide the precalculated YOLO neural network object detection annotations for all five cameras for the entire old data and the new ones. The dataset is suitable for developing mapping and navigation algorithms as well as the collision and object detection pipelines. The entire dataset is available as open-source under the MIT license.
- ItemHuman Detection in Depth Map Created from Point Cloud(2022-04-02) Ligocki, Adam; Žalud, LuděkThis paper deals with human detection in the LiDAR data using the YOLO object detection neural network architecture. RGB-based object detection is the most studied topic in the field of neural networks and autonomous agents. However, these models are very sensitive to even minor changes in the weather or light conditions if the training data do not cover these situations. This paper proposes to use the LiDAR data as a redundant, and more condition invariant source of object detections around the autonomous agent. We used the publically available real-traffic dataset that simultaneously captures data from RGB camera and 3D LiDAR sensors during the clear-sky day and rainy night time and we aggregate the LiDAR data for a short period to increase the density of the point cloud. Later we projected these point cloud by several projection models, like pinhole camera model, cylindrical projection, and bird-view projection, into the 2D image frame, and we annotated all the images. As the main experiment, we trained the several YOLOv5 neural networks on the data captured during the day and validate the models on the mixed day and night data to study the robustness and information gain during the condition changes of the input data. The results show that the LiDAR-based models provide significantly better performance during the changed weather conditions than the RGB-based models.