control applications are increasingly sampled non-equidistantly in time, including in motion control, networked control, resource-aware control, and event-triggered control. Some of these applications use measurement ...
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control applications are increasingly sampled non-equidistantly in time, including in motion control, networked control, resource-aware control, and event-triggered control. Some of these applications use measurement devices that sample equidistantly in the amplitude domain. The aim of this paper is to develop a non-parametric estimator of the impulse response of continuous-time systems based on such sampling strategy, known as Lebesgue-sampling. To this end, kernel methods are developed to formulate an algorithm that adequately takes into account the output intersample behavior, which ultimately leads to more accurate models and more efficient output sampling compared to the standard approach. The efficacy of this method is demonstrated through a mass-spring damper case study.
This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the dist...
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Increasing the operational efficiency of agricultural machines is essential by the use of artificial intelligence (AI)-based navigation, planning, and control algorithms to handle the increasing demand for food produc...
With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the hi...
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We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of constructing a semi-definite program subject ...
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作者：
Możaryn, JakubDepartment of Mechatronics
Institute of Automatic Control and Robotics Warsaw Univeristy of Technology ul. Sw. A. Boboli 8 Warsaw02-525 Poland
The electronic skin described in the article comprises screen-printed graphene-based sensors, intended to be used for robotic applications. The precise mathematical model allowing the touch pressure estimation is requ...
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Electric Vehicles (EVs) become very important issue and gained attention due to many reasons like its economic price, saving environment and more reliable. In this study, controlling speed for EV is utilized by tracki...
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作者：
Kacper PodbuckiTomasz MarciniakFaculty of Automatic Control
Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawła II 24 Poznan University of Technology Poznań Poland
Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct directio...
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ISBN:
(数字)9788362065486
ISBN:
(纸本)9798350373806
Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct direction of movement of the measuring device. This article presents research on a solution for the initial detection of glowing airport lamps based on camera images. The impact of the selection of parameters and image processing methods on the prepared data set was assessed. The histogram filtration method was introduced to improve the effectiveness of airport lamp localization. The proposed solution was investigated in different weather and daytime conditions. The overall accuracy of the proposed solution is more than ${9 0 \%}$.
In this article, a system for automatic recognition, including detection and classification, of emergency vehicles based on images from video recorders is proposed. The system utilizes YOLO v8 artificial neural networ...
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ISBN:
(数字)9788362065486
ISBN:
(纸本)9798350373806
In this article, a system for automatic recognition, including detection and classification, of emergency vehicles based on images from video recorders is proposed. The system utilizes YOLO v8 artificial neural network. Recognition accuracy tests were conducted on a specially prepared database of frames from real recordings. It includes marked and unmarked police vehicles (which are very difficult to distinguish and typically not included in automatic recognition systems), fire, ambulance, military vehicles and other reference images. The experiments concerned the recognition of vehicle types and the state of emergency lighting. The highest value of total (for all classes) F1 measure is over 86%. In selected classes the F1 reaches 91%, while precision is 94% and sensitivity is 89%. They can be considered as satisfactory results, what indicates the possibility of using the presented system in practice.
In this article, an automatic recognition system, of objects that threaten the safety of vehicle users is proposed. These objects are detected in front of the vehicle’s windshield based on images from video recorders...
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ISBN:
(数字)9788362065486
ISBN:
(纸本)9798350373806
In this article, an automatic recognition system, of objects that threaten the safety of vehicle users is proposed. These objects are detected in front of the vehicle’s windshield based on images from video recorders and then classified. The tests were conducted using artificial neural networks on a specially prepared database of frames from real recordings. Recognized objects include: car wheels, car parts, birds, stones and ice. They were recognized in single- and multi-class detections for various parameters of the network model. Detection efficiency of $95 \%$ was achieved in the best case.
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