Áron Ballagi - Academia.edu (original) (raw)

Papers by Áron Ballagi

This Innovative Practice Work in Progress paper presents a novel educational project, aiming at t... more This Innovative Practice Work in Progress paper presents a novel educational project, aiming at the development and implementation of a professional, standardized, internationally accepted system for training and certifying teachers, school students and young people in Artificial Intelligence (AI) and Robotics. In recent years, AI and Robotics have become major topics with a huge impact not only on our everyday life but also on the working environment. Hence, sound knowledge about principles and concepts of AI and Robotics are key skills for the 21st century. Nonetheless, hardly any systematic approaches exist that focus on teaching AI/Robotics principles at K-12 level, addressing both teachers and students. In order to meet this challenge, the European Driving License for Robots and Intelligent Systems is under development. It is based on a number of previously implemented and evaluated projects and comprises teaching curricula and training modules for AI/Robotics, following a competency based, blended learning approach. Additionally, a certification system proves peoples’ competencies acquired during the training. By applying this innovative approach - a standardized and widely recognized training and certification system for AI and Robotics at K-12 level for both teachers and students – we envision to foster AI/Robotics literacy on a broad basis.

Acta technica Jaurinensis, 2008

2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI)

2022 IEEE 1st International Conference on Internet of Digital Reality (IoD)

This paper presents some examples for fuzzy communication and intention guessing from the real li... more This paper presents some examples for fuzzy communication and intention guessing from the real life to the cooperation of intelligent mobile robots. In a special experimental environment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. Fuzzy signature can be considered as special multidimensional fuzzy data. Some of the dimensions are interrelated in the sense that they form sub-group of variables, which jointly determine some feature on higher level. Thus, complex objects and situations can be described by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems.

KI - Künstliche Intelligenz, 2021

This article presents a novel educational project aiming at the development and implementation of... more This article presents a novel educational project aiming at the development and implementation of a professional, standardized, internationally accepted system for training and certifying teachers, school students and young people in Artificial Intelligence (AI) and Robotics. In recent years, AI and Robotics have become major topics with a huge impact not only on our everyday life but also on the working environment. Hence, sound knowledge about principles and concepts of AI and Robotics are key skills for this century. Nonetheless, hardly any systematic approaches exist that focus on teaching principles of intelligent systems at K-12 level, addressing students as well as teachers who act as multipliers. In order to meet this challenge, theEuropean Driving License for Robots and Intelligent Systems—EDLRISwas developed. It is based on a number of previously implemented and evaluated projects and comprises teaching curricula and training modules for AI and Robotics, following a compet...

Computers

Bus driver distraction and cognitive load lead to higher accident risk. Driver distraction source... more Bus driver distraction and cognitive load lead to higher accident risk. Driver distraction sources and complex physical and psychological effects must be recognized and analyzed in real-world driving conditions to reduce risk and enhance overall road safety. The implementation of a camera-based system utilizing computer vision for face recognition emerges as a highly viable and effective driver monitoring approach applicable in public transport. Reliable, accurate, and unnoticeable software solutions need to be developed to reach the appropriate robustness of the system. The reliability of data recording depends mainly on external factors, such as vibration, camera lens contamination, lighting conditions, and other optical performance degradations. The current study introduces Capsule Networks (CapsNets) for image processing and face detection tasks. The authors’ goal is to create a fast and accurate system compared to state-of-the-art Neural Network (NN) algorithms. Based on the se...

Cleaner Engineering and Technology

2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI)

Nowadays convolutional neural networks (CNNs) have produced the state-of-the-art performance in i... more Nowadays convolutional neural networks (CNNs) have produced the state-of-the-art performance in image classification and segmentation tasks. The efficiency of the neural networks is one of the bests when the testing samples are close to the training data. Nevertheless, if we make some transformation on the dataset, the performance of the convolutional neural network reduced. Recently, capsule networks (CapsNet) have been introduced to solve some of the problems of neural networks. In this paper we examine the effectiveness of three different capsule based neural networks, and compare the performance when the parameters of the dynamic routing algorithm and the squashing function are modified.

2020 2nd IEEE International Conference on Gridding and Polytope Based Modelling and Control (GPMC), 2020

In this paper, a novel approach to the local planning of mobile robots and autonomous vehicles is... more In this paper, a novel approach to the local planning of mobile robots and autonomous vehicles is discussed. This paper introduces a motion planning architecture utilizing both a conventional (Hybrid A*) and a learning-based planner, inspired by the recent results of reinforcement learning. The presented approach relies on a grid-based representation of the environment which is simultaneously used for planning and learning of such trajectories. The representation grid is derived from a quadtree representation of the environment and the definition is extended with convex polytopic description, to produce grid-based and Voronoi diagrams. The paper also discusses the possible integration of more sophisticated soft-computing-based control, like TP-model transformation as a basis for the heuristics used by motion planning components.

2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES), 2018

As increasing use of neural networks (NN) and deep-learning (DL) can be observed in various field... more As increasing use of neural networks (NN) and deep-learning (DL) can be observed in various fields, such as voice and image recognition, control, translation, data processing, function approximation, etc. These technologies can also be applied in a specific domain of experimental vehicles. This paper presents and summarizes our recent practical experiences gained during the usage of neural network as sensing and perception subsystem in an experimental vehicle. The paper does not targets general NN problems, only focuses on the narrow subdomain. The current paper also reviews and evaluates the available hyper parameter tunings, optimizers and neural network architectures and proposes tested solutions for enhanced performance. All of the used datasets, source codes and additional materials is available online.

Abstract—This paper presents a novel action selection method for multi robot task sharing problem... more Abstract—This paper presents a novel action selection method for multi robot task sharing problem. Two autonomous mobile robots try to cooperate for push a box to a goal position. Both robots equipped with object and goal sensing, but do not have explicit communication ability. We explore the use of fuzzy signatures and decision making system to intention guessing and efficient action selection. Virtual reality simulation is used to build and test our proposed algorithm.

2019 IEEE 15th International Scientific Conference on Informatics, 2019

At the Széchenyi István University we develop an autonomous racing car for the Shell Eco-marathon... more At the Széchenyi István University we develop an autonomous racing car for the Shell Eco-marathon. One of the main tasks is to create a neural network which is segment the road surface, the protective barriers and other components of the race track. The difficulty of this task, that there is no a right dataset for this special issue. Only a limited size dataset available, therefore, we would like to expands this dataset with computer generated training images, which comes from a virtual city environment. In this work we want to examine the effect of computer generated images on the efficiency of different neural networks. In the training process real images and computer generated virtual images are mixed in several different ways. After that, three different neural network architecture for road surface and road barrier detection are trained. Experiences shows how to mixing datasets and how they can improve efficiency.

2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES), 2020

This paper presents a model-oriented toolset developed for academic autonomous vehicle projects. ... more This paper presents a model-oriented toolset developed for academic autonomous vehicle projects. Typical parameters are modeled into a structured domain model, which provides an organized view of the target vehicle. This model can be used to generate the bridge software linking low-level control software (e.g. CAN network) with high-level middleware frameworks. Other software items can be also originated from this model, including the configuration of deployed sensory components and simulation description. Code generation is performed via transforming the vehicle domain model instance into other specific domains (e.g. general kinematic description from vehicle description). As a result, a tool is provided which can be used to define a vehicle configuration in a textual format. The generators create code interfacing the open-source Robot Operating System (ROS).