TY - JOUR AU - Gincsainé Szádeczky-Kardoss, Emese AU - Varga-Berta, Tamás AU - Kiss, Bálint AU - Fazekas, Csaba TI - Sensor Selection for Mechatronic Systems Based on Closed-Loop Control Simulations JF - MECHANISMS AND MACHINE SCIENCE J2 - MECHANISMS AND MACHINE SCIENCE VL - 154 PY - 2024 SP - 107 EP - 117 PG - 11 SN - 2211-0984 DO - 10.1007/978-3-031-51085-4_10 UR - https://m2.mtmt.hu/api/publication/34822039 ID - 34822039 N1 - Megjelent a 25th International Symposium on Measurements and Control in Robotics : Proceedings of ISMCR 2023 című kötetben, Hardcover ISBN: 978-3-031-51084-7; Softcover ISBN: 978-3-031-51087-8; eBook ISBN: 978-3-031-51085-4 AB - The goal of the paper is to present a tool, which can be used for the selection of sensors in a closed-loop control of a mechatronic system. Several sensor parameters (such as noise power or delay) are simulated and their effects on the whole system’s performance are analyzed. For the simulations, Matlab-Simulink environment is applied. The simulated data are then used to estimate the transfer function of the whole closed-loop system with a controller. The services of the System Identification toolbox are appropriate for this task. If the specifications are given as the required damping and bandwidth of the system, the tool estimates the sensor parameters, which can ensure the desired performance. Some simulation results demonstrate the workflow of our tool, which was implemented using the App Designer of Matlab. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. LA - English DB - MTMT ER - TY - JOUR AU - Szőts, János AU - Gyenes, Zoltán AU - Gincsainé Szádeczky-Kardoss, Emese AU - Bölöni, Ladislau AU - Harmati, István TI - The Emergency Braking Game: a game theoretic approach for maneuvering in a dense crowd of pedestrians JF - ROBOMECH JOURNAL J2 - ROBOMECH JOURNAL VL - 11 PY - 2024 IS - 1 PG - 17 SN - 2197-4225 DO - 10.1186/s40648-023-00266-8 UR - https://m2.mtmt.hu/api/publication/34685221 ID - 34685221 N1 - Department of Control Engineering and Information Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary Department of Computer Science, University of Central Florida, 4328 Scorpius St, Orlando, FL 32816, United States Export Date: 8 March 2024 Correspondence Address: Szőts, J.; Department of Control Engineering and Information Technology, Műegyetem rkp. 3., Hungary; email: szotsjanos@iit.bme.hu Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding text 1: Open access funding provided by Budapest University of Technology and Economics. The research reported in this paper is part of project no. BME-NVA-02, implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021 funding scheme. Funding text 2: Supported by the ÚNKP-23-4-I-BME-360 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. AB - We introduce an algorithm that maneuvers a vehicle through an area with randomly moving pedestrians. In non-critical situations, our strategy is to avoid pedestrians by steering, whereas dangerously moving pedestrians are avoided by braking, possibly coming to a complete stop. The distinction between non-critical and dangerous situations, as well as proof of safety, is based on a continuous optimization problem that we define. In this abstract problem, called Emergency Braking Game, one pedestrian is actively trying to collide with a continuously decelerating car. We show how to determine the outcome of the game based on the initial states of the car and the pedestrian. Using this information, our algorithm can initiate deceleration in the real scenario in time to avoid collision. The method’s safety is proven theoretically, and its efficiency is shown in simulations with randomly moving pedestrians. LA - English DB - MTMT ER - TY - JOUR AU - Gyenes, Zoltán AU - Pajkos, Barnabás AU - Bölöni, Ladislau AU - Gincsainé Szádeczky-Kardoss, Emese TI - Motion Planning for Mobile Robots Using Uncertain Obstacle Estimation JF - IEEE ACCESS J2 - IEEE ACCESS VL - 12 PY - 2024 SP - 16856 EP - 16867 PG - 12 SN - 2169-3536 DO - 10.1109/ACCESS.2024.3359156 UR - https://m2.mtmt.hu/api/publication/34560878 ID - 34560878 N1 - Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics, Department of Control Engineering and Information Technology, Budapest, 1111, Hungary University of Central Florida, Department of Computer Science, Orlando, FL 32816, United States Export Date: 18 March 2024 Correspondence Address: Gyenes, Z.; Budapest University of Technology and Economics, Hungary; email: zgyenes@iit.bme.hu AB - The collision-free movement for a mobile robot in the presence of dynamic obstacles remains a significant challenge. In addition to self-localization, we also need to worry about the location of the moving obstacles, taking into account the noise in the sensors and the uncertainty in the movement of these obstacles. In this paper, we propose an approach for omnidirectional robot maneuvering in a 2D workspace that combines a Particle Filter for the estimation of the obstacles from LiDAR data and a variation of the Velocity Obstacles (VO) technique. The position and the velocity vector of the obstacles can be perceived by the Particles Filter and an uncertainty degree is also calculated. These outputs are combined with the VO algorithm to achieve motion planning that takes into account the current level of uncertainty as well as a cost function that expresses the risk tolerance of the user. We validate the approach in simulation and in experiments with a physical robot. Authors LA - English DB - MTMT ER - TY - JOUR AU - Gyenes, Zoltán AU - Bölöni, L. AU - Gincsainé Szádeczky-Kardoss, Emese TI - Exploring the Use of Particle and Kalman Filters for Obstacle Detection in Mobile Robots JF - PERIODICA POLYTECHNICA-ELECTRICAL ENGINEERING AND COMPUTER SCIENCE J2 - PERIOD POLYTECH ELECTR ENG COMP SCI VL - 67 PY - 2023 IS - 4 SP - 384 EP - 393 PG - 10 SN - 2064-5260 DO - 10.3311/PPee.21969 UR - https://m2.mtmt.hu/api/publication/34342471 ID - 34342471 N1 - Department of Control Engineering and Information Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Muegyetem rkp. 3., Budapest, H-1111, Hungary Department of Computer Science, University of Central Florida, 4328 Scorpius St, Orlando, FL 32816-2362, United States Export Date: 16 November 2023 Correspondence Address: Gyenes, Z.; Department of Control Engineering and Information Technology, Muegyetem rkp. 3., Hungary; email: zgyenes@iit.bme.hu AB - The present study aims to explore the adaptation of estimation methodologies, specifically Particle filters and Kalman filters, for the purpose of determining the position and velocity vector of obstacles within the operational workspace of mobile robots. These algorithms are commonly employed in the motion planning tasks of mobile robots for the estimation of their own position. The proposed methodology utilizes LiDAR sensor data to estimate the position vectors and calculate the velocity vectors of obstacles. Additionally, an uncertainty parameter can be determined using the introduced perception method. The performance of the newly adapted algorithms is evaluated through comparison of the absolute error in position and velocity vector estimations. LA - English DB - MTMT ER - TY - JOUR AU - Gyenes, Zoltán AU - Bölöni, Ladislau AU - Gincsainé Szádeczky-Kardoss, Emese TI - Can Genetic Algorithms Be Used for Real-Time Obstacle Avoidance for LiDAR-Equipped Mobile Robots? JF - SENSORS J2 - SENSORS-BASEL VL - 23 PY - 2023 IS - 6 SN - 1424-8220 DO - 10.3390/s23063039 UR - https://m2.mtmt.hu/api/publication/33698172 ID - 33698172 N1 - Department of Computer Science, University of Central Florida, 4328 Scorpius St., Orlando, FL 32816, United States Department of Control Engineering and Information Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary Export Date: 11 April 2023 Correspondence Address: Bölöni, L.; Department of Computer Science, 4328 Scorpius St., United States; email: ladislau.boloni@ucf.edu AB - Despite significant progress in robot hardware, the number of mobile robots deployed in public spaces remains low. One of the challenges hindering a wider deployment is that even if a robot can build a map of the environment, for instance through the use of LiDAR sensors, it also needs to calculate, in real time, a smooth trajectory that avoids both static and mobile obstacles. Considering this scenario, in this paper we investigate whether genetic algorithms can play a role in real-time obstacle avoidance. Historically, the typical use of genetic algorithms was in offline optimization. To investigate whether an online, real-time deployment is possible, we create a family of algorithms called GAVO that combines genetic algorithms with the velocity obstacle model. Through a series of experiments, we show that a carefully chosen chromosome representation and parametrization can achieve real-time performance on the obstacle avoidance problem. LA - English DB - MTMT ER - TY - CHAP AU - Gyenes, Zoltán AU - Ladislau, Bölöni AU - Gincsainé Szádeczky-Kardoss, Emese TI - Perception of obstacles at mobile robot's motion planning algorithm using Kalman filter and Particle filter T2 - Proceedings of the Workshop on the Advances of Information Technology 2023 PB - BME Irányítástechnika és Informatika Tanszék CY - Budapest SN - 9789634218968 PY - 2023 SP - 86 EP - 91 PG - 6 UR - https://m2.mtmt.hu/api/publication/33625723 ID - 33625723 LA - English DB - MTMT ER - TY - CHAP AU - Lévay, Mátyás AU - Finta, Barnabás AU - Szabó, Dániel AU - Ádám, Anna Barbara AU - Gincsainé Szádeczky-Kardoss, Emese AU - Fazekas, Csaba TI - Effect of sensor parameters in the closed-loop control of a mechatronic system T2 - Proceedings of the Workshop on the Advances of Information Technology 2023 PB - BME Irányítástechnika és Informatika Tanszék CY - Budapest SN - 9789634218968 PY - 2023 SP - 66 EP - 70 PG - 5 UR - https://m2.mtmt.hu/api/publication/33625714 ID - 33625714 LA - English DB - MTMT ER - TY - CHAP AU - Szabó, Dániel AU - Gincsainé Szádeczky-Kardoss, Emese TI - A proposal for an FPGA-based graphical pipeline for virtual depth image generation T2 - 2022 International Symposium on Measurement and Control in Robotics (ISMCR) PB - IEEE SN - 9781665454964 PY - 2022 SP - 1 EP - 5 PG - 5 DO - 10.1109/ISMCR56534.2022.9950575 UR - https://m2.mtmt.hu/api/publication/33419528 ID - 33419528 N1 - Funding Agency and Grant Number: Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund [TKP2021] Funding text: The research reported in this paper is part of project no. BME-NVA-02, implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021 funding scheme. AB - Currently, industrial robots can follow well-defined, repetitive tasks, which can substantially increase the productivity of the manufacturing processes. But the reaction to a dynamically changing environment is a frequently studied part of robotics. In our paper, we propose an FPGA-based virtual depth image generation process, which implements a modified graphical pipeline on the FPGA. Using the manipulator's current configuration and camera parameters, the robot's 3D model is transformed and projected into a 2D plane. During the rasterization stage, a virtual depth image is generated by determining the depth values for all the pixel coordinates. Although the FPGAs have limited capability for implementing a generic graphical pipeline, the described task-specific optimizations in the paper can provide a fast and energy-efficient implementation. LA - English DB - MTMT ER - TY - CHAP AU - Ádám, Anna Barbara AU - Gincsainé Szádeczky-Kardoss, Emese ED - IEEE, , TI - Mapping an unknown environment with explored area-detection T2 - 2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) PB - IEEE CY - Piscataway (NJ) SN - 9781665468589 PY - 2022 SP - 23 EP - 28 PG - 6 DO - 10.1109/MMAR55195.2022.9874324 UR - https://m2.mtmt.hu/api/publication/33087089 ID - 33087089 AB - Mapping and exploring an unknown area is required in many fields of life. There exist rescue robots, which are able to explore dangerous, hard to reach areas. Other robots are used for exploring areas in order to find minerals or oils. This paper presents a method, which uses a lidar sensor for scanning the environment. The presented exploration method is applicable in corridor environments. The exploration path is planned by using an n-direction scanning detection algorithm. During the exploration, those areas are detected, which do not have to be visited again. In each step of the exploration, the currently seen area is approximated with a polygon, whose area is classified into two groups: those points, which do not have to be visited again, and those points, which should be visited again during the exploration. The exploration of example maps is presented. LA - English DB - MTMT ER - TY - CHAP AU - Kocsány, László AU - Gincsainé Szádeczky-Kardoss, Emese TI - Application of mixed graph traversal optimization for the vehicle routing problem T2 - 2022 European Control Conference (ECC) PB - European Control Association (EUCA) CY - Oxford SN - 9783907144077 PY - 2022 SP - 2149 EP - 2154 PG - 6 DO - 10.23919/ECC55457.2022.9838025 UR - https://m2.mtmt.hu/api/publication/33049255 ID - 33049255 N1 - Export Date: 13 September 2022 AB - The Vehicle routing problem (VRP) is widely discussed in the literature. The goal of the VRP is to provide an optimized traversal of a graph. This paper presents a mixed graph traversal optimization for the VRP. The mixed graph is a graph that contains both directed and undirected edges. The problem to be solved is a parking space search problem in a mixed graph where, from an initial location a vehicle first navigates to a zone, where the selected edges are located, and plans the traversal driving through all selected edges, and returning to the start of the exploration so that the path is repeatable. The paper shows, that the parking space search problem in a mixed graph can be reduced to a travelling salesman problem (TSP), for which an ant colony optimization (ACO) is implemented, to provide a solution, that is minimizing the total cost of the mixed graph traversal. LA - English DB - MTMT ER -