Iskanje po katalogu digitalne knjižnice

Opis: The integration of human-robot collaboration (HRC) into industrial and service environments demands efficient and adaptive robotic systems capable of executing diverse tasks, including pick-and-place operations. This paper investigates the application of Soft Actor-Critic (SAC) and Conservative Q-Learning (CQL)—two deep reinforcement learning (DRL) algorithms—for the learning and optimization of pick-and-place actions within HRC scenarios. By leveraging SAC’s capability to balance exploration and exploitation, the robot autonomously learns to perform pick-and-place tasks while adapting to dynamic environments and human interactions. Moreover, the integration of CQL ensures more stable learning by mitigating Q-value overestimation, which proves particularly advantageous in offline and suboptimal data scenarios. The combined use of CQL and SAC enhances policy robustness, facilitating safer and more efficient decision-making in continually evolving environments. The proposed framework combines simulation-based training with transfer learning techniques, enabling seamless deployment in real-world environments. The critical challenge of trajectory completion is addressed through a meticulously designed reward function that promotes efficiency, precision, and safety. Experimental validation demonstrates a 100 % success rate in simulation and an 80 % success rate on real hardware, confirming the practical viability of the proposed model. This work underscores the pivotal role of DRL in enhancing the functionality of collaborative robotic systems, illustrating its applicability across a range of industrial environments.
Ključne besede: human-robot collaboration, robot learning, deep reinforcement learning, soft actor-critic algorithm, Conservative Q-learning, robot manipulation tasks
Objavljeno v DKUM: 16.01.2026; Ogledov: 0; Prenosov: 0
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Opis: Purpose: The purpose of the research was to explore how virtual exchanges can empower teachers of engineering and technology and practical subjects. The aim was to determine whether and how these teachers see virtual exchanges as an opportunity for personal and professional development, improvement of teaching, and exchange of good practices. Findings: The research was conducted at the beginning of the 2023/2024 school year with interviews conducted via online video calls. The sample included 16 teachers and 2 students (future teachers of engineering and technology). Before the interviews, participants received an introductory presentation of the concept of virtual exchanges and then answered four pre-prepared questions that focused on the perception and meaning of these exchanges for teachers. Originality/value: The paper is important because it focuses on a less researched area -the use of virtual exchanges in the context of technical education that includes practical work. The research fills a gap in the literature and offers valuable insights for the development of international collaboration among teachers of technical subjects and for the design of supporting platforms, tools and policies that would enable and promote this collaboration.
Ključne besede: virtual exchanges, education, teacher professional development, intercultural collaboration, practice-based pedagogy
Objavljeno v DKUM: 21.10.2025; Ogledov: 0; Prenosov: 8
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Opis: This study deals with berth allocation for Maritime Autonomous Surface Ships (MASSs) in the context of the mixed operation of MASSs and manned vessels from the perspective of port-shipping companies’ collaboration. Two berth allocation strategies, namely the separated-type and the mixed-type, are proposed in this article. Two mixed integer nonlinear programming models aimed at minimizing the total docking cost of the vessels in the port and the waiting time for berths are developed and solved using Gurobi, respectively. A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. Several experiments are conducted to test the effectiveness of the model and to draw insights for commercializing autonomous vessels. The presented results show that multi-objective modeling and optimization should be conducted from the collaboration of port-shipping companies, which is more efficient from the perspective of shipping companies or ports, respectively. When berth resources are limited or there is a high requirement for operational safety, the separated-type berth allocation strategy is more efficient. When the number of MASS-dedicated berths reaches a certain proportion, the total docking cost of the vessel no longer changes, indicating that more dedicated berths are not better.
Ključne besede: maritime autonomous surface ship (MASS), mixed operation scenarios, berth allocation, mixed integer programming, simulated annealing algorithm, port-shipping companies’ collaboration
Objavljeno v DKUM: 18.06.2025; Ogledov: 0; Prenosov: 2
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Opis: Collaboration patterns offer important insights into how scientific breakthroughs and innovations emerge in small and large research groups. However, links in traditional networks account only for pairwise interactions, thus making the framework best suited for the description of two-person collaborations, but not for collaborations in larger groups. We therefore study higher-order scientific collaboration networks where a single link can connect more than two individuals, which is a natural description of collaborations entailing three or more people. We also consider different layers of these networks depending on the total number of collaborators, from one upwards. By doing so, we obtain novel microscopic insights into the representativeness of researchers within different teams and their links with others. In particular, we can follow the maturation process of the main topological features of collaboration networks, as we consider the sequence of graphs obtained by progressively merging collaborations from smaller to bigger sizes starting from the single-author ones. We also perform the same analysis by using publications instead of researchers as network nodes, obtaining qualitatively the same insights and thus confirming their robustness. We use data from the arXiv to obtain results specific to the fields of physics, mathematics, and computer science, as well as to the entire coverage of research fields in the database.
Ključne besede: network, collaboration, social physics, complex system
Objavljeno v DKUM: 18.10.2024; Ogledov: 0; Prenosov: 3
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Opis: E-learning platforms have become more and more complex. Their functionality included in learning management systems is extended with collaborative platforms, which allow better communication, group collaboration, and face-to-face lectures. Universities are facing the challenge of advanced use of these platforms to fulfil sustainable learning goals. Better usability and attractiveness became essential in successful e-learning platforms, especially due to the more intensive interactivity expected from students. In the study, we researched the user experience of students who have used Moodle, Microsoft Teams, and Google Meet. User experience is, in most cases, connected with a person’s perception, person’s feelings, and satisfaction with the platform used. Data were collected using a standard UEQ questionnaire. With this research, we examined whether user experience factors: perceived efficiency, perceived perspicuity, perceived dependability, perceived stimulation, and perceived novelty affect perceived attractiveness, which is an important factor in the sustainability of e-learning tools. The collected data were processed using SmartPLS. The research study showed that all studied factors have a statistically significant impact on perceived attractiveness. Factor perceived stimulation has the strongest statistically significant impact on the perceived attractiveness of e-learning platforms, followed by perceived efficiency, perceived perspicuity, perceived novelty, and perceived dependability.
Ključne besede: e-learning platform, collaboration platform, usability, user experience
Objavljeno v DKUM: 09.07.2024; Ogledov: 116; Prenosov: 12
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