In engineering and scientific practice, models of uncertain discrete control systems can be described by interval systems and interval optimization problems over extremal algebra. A manufacture control example is give...
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ISBN:
(纸本)9798350386783;9798350386776
In engineering and scientific practice, models of uncertain discrete control systems can be described by interval systems and interval optimization problems over extremal algebra. A manufacture control example is given to show the motivation and the application of AE solutions. Full characterizations are established. Moreover, the concepts and characterizations of traditional solutions are also extended to max-min algebra, as special cases of AE solutions.
Pathfinding algorithms hold significant importance in navigation systems, robotics, and gaming. this paper introduces an Interactive Pathfinding Visualizer developed using HTML, CSS, and JavaScript, which allows users...
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the manufacturing landscape is rapidly evolving, being characterized by the emergence of Industry 5.0, leading to a growing recognition of the importance of a human -centered, sustainable and resilient approach. In re...
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the manufacturing landscape is rapidly evolving, being characterized by the emergence of Industry 5.0, leading to a growing recognition of the importance of a human -centered, sustainable and resilient approach. In response to these needs, collaborative robotics has emerged as a promising solution to enhance flexibility in industrial operations, while ensuring a higher level of safety. Cobots enable human-robot collaboration without the need for physical barriers, reduce the footprint of the robotic station, and foster a closer working relationship between humans and machines. this article focuses on an application of collaborative robotics in end-of-line industrial operations, specifically in the unloading of products from an automatic machine. By managing repetitive tasks, such as placing the trays near the end of the line of the automatic machine, waiting for them to be filled, and placing them on a trolley, which will then be moved by the human operator, the robot significantly improves efficiency. the proposed solution involves alternating the placement of trays in two rack trolleys, allowing the worker to replace the full trolleys with empty ones at his own timing. the paper examines the potential advantages of using a human -centric approach that emphasizes operator empowerment and human oversight: the collaborative robotic cell and the automation implemented free the workers from the low value-added operations and allow them to oversee and manage multiple machines simultaneously, thus enhancing productivity. the approach behind this proposal is to keep robotic tasks simple, easily reprogrammable and modular, while empowering the human operator to engage in supervision, decision -making, and problem-solving tasks. this collaboration allows the operator to assume a supervisory role, organizing production based on identified needs, and elevating their involvement to production line management tasks.
Robotic systemsthat utilize machine learning typically demand a large amount of highly accurate data for model training and performance improvement. Crowdsourcing provides researchers with a low-cost opportunity to g...
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ISBN:
(纸本)9789819616138;9789819616145
Robotic systemsthat utilize machine learning typically demand a large amount of highly accurate data for model training and performance improvement. Crowdsourcing provides researchers with a low-cost opportunity to gather diverse data from around the world. these data can significantly enhance robots' capabilities in terms of perception, decision-making, and interaction while also accelerating the optimization of machine learning models. However, owing to variations in the skills, experience, and personal biases of crowdsourcing participants, noise and redundancy are often introduced during data collection, compromising data quality and weakening the effectiveness of crowdsourcing data in improving robotic systems. To address this issue, confidence learning (CL) technology was first introduced to filter out erroneous or unreliable crowdsourced data. By analyzing the explicit or implicit relationships between workers and tasks, graph neural networks (GNNs) can be used to leverage node embeddings to infer the true labels of annotated data, improving accuracy and reliability. the experiments were conducted on real crowdsourced annotation datasets, covering 13 real-world application scenarios. the results demonstrate that after applying these processing steps, the accuracy of the data labels is significantly improved, providing a more robust data foundation for training robotic systems.
the field of traditional mobile robot navigation has undergone a gradual transformation, evolving into a standardized and procedural research domain. through a fresh cognitive perspective on this navigation process, a...
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In the contemporary age of advanced technology, image processing plays a vital role as an efficient and indispensable tool across industries, enterprises, monitoring systems, and various applications. this study focus...
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In the rapidly evolving landscape of ro botics, Large Language Models (LLMs) have emerged as a pivotal tool in enhancing the capabilities of robotic systems. this paper introduces a unified LLM-based framework tailore...
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Digital marketing has transformed referral marketing, revealing limitations in traditional centralized systems such as trust, transparency, and efficiency, however, the potential advantages of decentralized systems re...
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ISBN:
(纸本)9798350317824
Digital marketing has transformed referral marketing, revealing limitations in traditional centralized systems such as trust, transparency, and efficiency, however, the potential advantages of decentralized systems remain underexplored. this paper investigates the feasibility of a high-volume, decentralized referral system. the approach assesses smart contract prototypes for cost-effectiveness and performance in high-user engagement scenarios in different EVM-compatible blockchains and referral strategies, such as multilevel referrals. Findings confirm the technical viability as a blueprint for designing and implementing similar systems, highlighting challenges in real-world deployments, such as Sybil attacks, and the interplay between technical and economical design factors.
Federated Byzantine Agreement systems (FBASs) offer a solution to consensus in permissionless systems by adapting the well-studied Byzantine agreement model to permissionless consensus. Unlike its counterparts in the ...
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ISBN:
(纸本)9798350317824
Federated Byzantine Agreement systems (FBASs) offer a solution to consensus in permissionless systems by adapting the well-studied Byzantine agreement model to permissionless consensus. Unlike its counterparts in the context of permissionless consensus, the FBAS system model does not offer validating nodes protocol-level incentives although they are entrusted with safeguarding and ensuring the functionality of the system. Multiple studies have reported on the small number of active validators in these systems leading to some concerns about their resilience. To this end, this paper studies how rewards can be distributed in FBASs and presents a fair reward distribution function for FBASs. the challenge is that, on the one hand, consensus in an FBAS is found jointly between all nodes and, on the other hand, nodes do not all contribute equally to this process. We draw on game-theoretic methods to quantify these contributions bearing the overall health of the FBAS in mind and present a fair reward distribution function which we evaluate based on a set of identified properties.
this paper introduces a dynamic output feedback control method based on model predictive control (MPC) strategy for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy systems. the proposed method considers the influence ...
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