Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing...
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robotics education plays a crucial role in developing STEM skills. However, university-level courses often emphasize theoretical learning, which can lead to decreased student engagement and motivation. In this paper, ...
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The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. ...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. Autonomous Mobile Robots (AMRs), with their advanced mobility and navigation capabilities, are a pillar of this transformation. However, their deployment in job shop environments adds complexity to the already challenging Job Shop Scheduling Problem (JSSP), expanding it to include task allocation, robot scheduling, and travel time optimization, creating a multi-faceted, non-deterministic polynomial-time hardness (NP-hard) problem. Traditional approaches such as heuristics, meta-heuristics, and mixed integer linear programming (MILP) are commonly used. Recent AI advancements, particularly large language models (LLM), have shown potential in addressing these scheduling challenges due to significant improvements in reasoning and decision-making from textual data. This paper examines the application of LLM to tackle scheduling complexities in smart job shops with mobile robots. Guided by tailored prompts inserted manually, LLM are employed to generate scheduling solutions, being these compared to an heuristic-based method. The results indicate that LLM currently have limitations in solving complex combinatorial problems, such as task scheduling with mobile robots. Due to issues with consistency and repeatability, they are not yet reliable enough for practical implementation in industrial environments. However, they offer a promising foundation for augmenting traditional approaches in the future.
robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry. Apart from cases were robots are expected to completel...
robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry. Apart from cases were robots are expected to completely replace them, humans will largely benefit from real interactions with such robots. This is not only true for complex interaction scenarios like robots serving as guides, companions or members in a team, but also for more predefined functions like autonomous transport of people or goods. More and more, robots need suitable interfaces to interact with humans in a way that humans feel comfortable and that takes into account the need for a certain transparency about actions taken. The paper describes the requirements and state-of-the-art for a human-centered robotics research and development, including verbal and non-verbal interaction, understanding and learning from each other, as well as ethical questions that have to be dealt with if robots will be included in our everyday environment, influencing human life and societies.
Bloch Surface Waves (BSW) consist of electromagnetic modes generated at the interface between a photonic crystal and an isotropic dielectric. This type of surface mode displays sharp resonances and high sensitivity to...
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Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understand...
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This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Wo...
This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution.
Radio-Frequency IDentification (RFID) technologies automate the identification of objects and persons, having several applications in retail, manufacturing, and intralogistics sectors. Several works explore the applic...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
Radio-Frequency IDentification (RFID) technologies automate the identification of objects and persons, having several applications in retail, manufacturing, and intralogistics sectors. Several works explore the application of RFID systems in robotics and intralogistics, focusing on locating robots, tags, and inventory management. This paper addresses the challenge of intralogistics cargo trolleys communicating their characteristics to an autonomous mobile robot through an RFID system. The robot must know the trolley's relative pose to avoid collisions with the surroundings. As a result, the passive tag on the cargo communicates information to the robot, including the base footprint of the trolley. The proposed RFID system includes the development of a controller board to interact with the frontend integrated circuit of an external antenna onboard the industrial mobile robot. Experimental results assess the system's readability distance in two distinct environments and with two different antenna modules. All the code and documentation are available in a public repository.
robotics education plays a crucial role in developing STEM skills. However, university-level courses often emphasize theoretical learning, which can lead to decreased student engagement and motivation. In this paper, ...
详细信息
ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
robotics education plays a crucial role in developing STEM skills. However, university-level courses often emphasize theoretical learning, which can lead to decreased student engagement and motivation. In this paper, we tackle the challenge of providing hands-on robotics experience in higher education by adapting a mobile robot originally designed for competitions to be used in laboratory classes. Our approach integrates real-world robot operation into coursework, bridging the gap between simulation and physical implementation while maintaining accessibility. The robot's software is developed using ROS, and its effectiveness is assessed through student surveys. The results indicate that the platform increases student engagement and interest in robotics topics. Furthermore, feedback from teachers is also collected and confirmed that the platform boosts students' confidence and understanding of robotics.
The growing reliance on e-commerce and the demand for efficient intralogistics operations have increased the need for automation, while labour shortages continue to pose significant challenges. When combined with the ...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
The growing reliance on e-commerce and the demand for efficient intralogistics operations have increased the need for automation, while labour shortages continue to pose significant challenges. When combined with the inherent risks of forklift operation, this circumstance prompted businesses to look for robotic solutions for intralogistics tasks. However, robots are still limited when they come across situations that are outside of their programming scope and often need assistance from humans. To achieve the long-term goal of enhancing intralogistics operation, we propose the development of a virtual reality-based teleoperation system that allows remote operation of robot forklifts with minimal latency. Considering the specificities of the teleoperation process and network dynamics, we conduct detailed modelling to analyse latency factors, optimise system performance, and ensure a seamless user experience. Experimental results on a mobile robot have shown that the proposed teleoperation system achieves an average glass-to-glass latency of 368 ms, with capturing latency contributing to approximately 60% of the total delay. The results also indicate that network os-cillations significantly impact image quality and user experience, emphasising the importance of a stable network infrastructure.
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