Chimney sweeping robot based on a pneumatic actuator

The need of improving the quality of professions led to the idea of simplification of processes during chimney sweeping. These processes have been essentially the same for tens of years. The goal of this paper is to bring an automation element into the chimney sweeping process, making the job easier for the chimney sweeper. In this paper, an essentially in-pipe robot is presented, which uses brushes to move while simultaneously cleaning the chimney or pipeline. The problem of the robot motion was reduced using an in-pipe robot due to the environments and obstacles that the robot has to face. An approach of using a pneumatic actuator for motion is presented along with the mechanical design. The next part of this paper is focused on the mathematical model of the robot motion, as well as its simulation and testing in the experimental pipeline. The simulations were compared with the experimental measurements and a few analyses were conducted describing the simulation model and its differences with the real robot, as well as considering certain parameters and their impact on the performance of the robot. The results are discussed at the end of the paper.Web of Science1111art. no. 487

Upgrade of biaxial mechatronic testing machine for cruciform specimens and verification by FEM analysis

This article deals with the modernization of an existing loading system for the analysis of elastic-plastic properties of sheet metals in plane stress. The identification of the beginning of plastic deformation of sheet metal in plane strain is important in the cold pressing of sheet metal and in the assessment of the load capacity of thin-walled structures in the automotive and aerospace industry. The design of the control structure of the hydraulic part of the loading system for cross testing was carried out to automatize the whole process of experimental evaluation. For this purpose, proportional pressure-reducing valves together with control electronics were designed. Thus, the loading system is a control system for which a control algorithm has been designed and implemented on a PC. A computer simulation was performed to verify the functionality of the load system. An FEM simulation was performed to verify the correctness of the proposed numerical models and to confirm the experimental results. A numerical nonlinear model of the selected material was applied for the specification of plastic deformations. From the results, it is possible to state the appropriateness of the used models as well as the appropriateness of using modernized equipment for subsequent analysis of the plastic deformation of cruciform specimens.Web of Science1010art. no. 91

Biped robot with unconventional kinematics

The article deals with the design of a robot with an unconventional kinematic structure, which is able to vertically stabilize the position of the robot base for the placement of sensors and handling superstructures. The robot concept was designed to have as few actuators as possible. The robot's kinematics was solved for the purpose of simulating the robot's movement and implementation into the robot's control system.Web of Science20225824581

Emergent trends in robotics and intelligent systems: where is the role of intelligent technologies in the next generation of robots?

What is the Role of Intelligent Technologies in the Next Generation of Robots ? This monograph gives answers to this question and presents emergent trends of Intelligent Systems and Robotics. After an introductory chapter celebrating 70 year of publishing the McCulloch Pitts model the book consists of the 2 parts „Robotics“ and „Intelligent Systems“. The aim of the book is to contribute to shift conventional robotics in which the robots perform repetitive, pre-programmed tasks to its intelligent form, where robots possess new cognitive skills with ability to learn and adapt to changing environment. A main focus is on Intelligent Systems, which show notable achievements in solving various problems in intelligent robotics. The book presents current trends and future directions bringing together Robotics and Computational Intelligence. The contributions include widespread experimental and theoretical results on intelligent robotics such as e.g. autonomous robotics, new robotic platforms, or talking robots

Experimental Evaluation of Cloud-Based Facial Emotion Recognition Services

The main goal of this paper is to perform an extensive analysis of the accuracy of six selected cloud-based facial emotion recognition services on three facial images datasets. The evaluation was performed on more than 33 000 images depicting eight different emotions. Results show that emotion recognition services show a varying level of accuracy over different types of datasets, having a lower accuracy for images of lower quality, but performing considerably better for images taken in ideal conditions. Based on these results we believe that cloud-based facial emotional recognition services do not have the expected accuracy for some use cases and therefore must be selected with care when developing a system that relies on emotion-based interactions

Psychophysiological Indicators for Modeling User Experience in Interactive Digital Entertainment

Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems—mainly the misinterpretation and temporal delay during longer experiments—and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods. We use a machine learning approach to model user experience using real-time data produced by the autonomic nervous system and involuntary psychophysiological responses. Multiple psychophysiological measures, such as heart rate, electrodermal activity, and respiratory activity, have been used in combination with self-reporting to prepare training sets for machine learning algorithms. The training data was collected from 31 participants during hour-long experiment sessions, where they played multiple video-games. Afterwards, we trained and compared the results of four different machine learning models, out of which the best one produced ∼96% accuracy. The results suggest that psychophysiological measures can indeed be used to assess the enjoyment of digital entertainment consumers