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2025 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Chopra, Vaibhav Rao, Chanakya Soni, Moksh Mishra, Prashant Plaksha University Computer Science & Artificial Intelligence Mohali India Plaksha University Data Science Economics & Business Mohali India Plaksha University Robotics & Cyber-Physical Systems Mohali India

ISBN: (纸本)9798331529833

The transportation of essential goods in mountainous regions faces severe logistical challenges and frequent disruptions. To mitigate these difficulties, transport companies often overload trucks, which, though cost-saving, significantly heightens the risk of accidents and mechanical failures. This paper presents the development of a device that detects overloaded and insecurely fastened loads on trucks and commercial vehicles. Using advanced load sensors, the device offers real-time monitoring of cargo weight distribution, alerting drivers and authorities to unsafe conditions. The initial prototype utilised two basic load cells and an Arduino microcontroller. The second version was enhanced with four load cells and extended sensors. This version was tested by placing an electric golf cart onto the prototype. Various loads were then added to the cart in different orientations to assess whether the system could accurately detect improper or excessive load conditions. © 2025 IEEE.

关键词： Trucks

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Secrecy Performance Review for IoT-based Cognitive Farming System

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Recent Patents on Engineering 2024年第7期18卷 66-75页

作者： Chopra, Khyati Alam, M. Afshar Department of CSE Jamia Hamdard University New Dehli India University School of Automation and Robotics GGSIPU New Delhi110032 India Department of Computer Science and Engineering Jamia Hamdard University New Delhi110062 India

Smart farm management has complex challenges;therefore, there is a need to improve the overall adaptability, profitability, and environmental soundness of the farming systems. Agricultural production can be enhanced with the help of IoT-based cognitive tools. The rapid increase in IoT-based smart systems has raised critical concerns about efficiently utilizing the wireless spectrum. To drastically bring the improvement in the utilization of the wireless spectrum, cognitive radio (CR) has emerged as an effective solution. The inherent openness and broadcast nature of the wireless medium have given rise to many security issues in cooperative networks. Information-theoretic security or physical layer security (PLS) is evolved as an efficacious wireless prototype for reliable transmissions to avert the eavesdropper from expropriating transmittal data on the wireless connections. Security is the key factor in these networks as they are exposed and active in be-havior, thus, are susceptible to fraudulent activities. In this patent study, we investigated the performance of the CR system in terms of secrecy and also examined the system in terms of diversity receipt and selection of relay. The secrecy outcome of channel state information at the sender was also studied. The detrimental effects of fading in cooperative networks were also extensively discussed. Cooperative diversity was examined by deploying MRC and SC strategies at receptors. It has been deduced that CSI knowledge at the sender also has an eloquent concussion on the secrecy of the cognitive system. © 2024 Bentham science Publishers.

关键词： Cognitive radio

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A modular control architecture for safe and robust robot operation and inspection in steep slope vineyards

A modular control architecture for safe and robust robot ope...

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2022 Informatik in den Naturwissenschaften, INFORMATIK 2022 - 2022 computer science in the Natural sciences, INFORMATIK 2022

作者： Gassen, Eike Wolf, Patrick Berns, Karsten Robotics Research Lab Department of Computer Science TU Kaiserslautern Germany

ISBN: (纸本)9783885797203

In fall line cultivation of vineyards, the vines are planted vertically to the hill's slope. Therefore, steep slope vineyards require a high amount of manual labor, doubling production costs. Working in such environments is exhausting and laborious. Therefore, autonomous robots should assist humans in reducing costs and increasing safety. However, current state-of-the-art robotic systems and control architectures are not designed to work in such harsh environments with extreme terrains. Therefore, this work proposes and modular control architecture for safe and robust autonomous working in steep slope environments. Tests in an authentic vineyard near the Moselle river in Germany prove the approach's feasibility and robustness. © 2022 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Cultivation

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Scanning the Issue - May 2025

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IEEE Transactions on Intelligent Transportation Systems 2025年第5期26卷 5627-5648页

作者： Simona Sacone Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

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Quantum Annealing for the Mechanics of Robot Inspectors on Electrical Transmission Lines' Conductors

Quantum Annealing for the Mechanics of Robot Inspectors on E...

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2024 International Conference on Control, robotics and Informatics, ICCRI 2024

作者： Salloum, Hadi Bahrami, Mohammad Reza Matevosian, Artem Gamershmidt, Sofia Jnadi, Ali Mazzara, Manuel Innopolis University Faculty of Computer Science and Engineering Innopolis Russia Innopolis University Cyber-physical systems lab Innopolis Russia Institute of Robotics and Computer Vision Innopolis University Innopolis Russia

ISBN: (纸本)9798350380309

This paper explores the integration of quantum computing, specifically quantum annealing, into robotics for inspecting electrical transmission lines. By using quantum annealing's computational power, we address the dynamics of robot inspectors on transmission line conductors, enhancing the computational efficiency of managing the movements of robot inspectors on transmission line conductors. The use of these robots is crucial for performing efficient and safe inspections. We discuss the mathematical foundations of quantum annealing, transforming differential equations governing robot dynamics into Ising model Hamiltonians suitable for quantum annealing devices. Through experiments using D-Wave's 'Advantage' quantum annealer, we demonstrate the viability of quantum annealing in solving complex robotics problems, paving the way for advanced applications in the field. © 2024 IEEE.

关键词： Ising model

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Configurable Dynamics of Electromagnetic Suspension by Fuzzy Takagi-Sugeno Controller 21st

Configurable Dynamics of Electromagnetic Suspension by Fuzzy...

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21st Polish Control Conference, PCC 2023

作者： Pilat, Adam Krzysztof Milanowski, Hubert Bieszczad, Rafal Sikora, Bartiomiej Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH-University of Science and Technology Krakow Poland

ISBN: (纸本)9783031351693

This elaboration presents the synthesis of the Takagi-Sugeno type Fuzzy Logic controller realizing the programmable parameters of the state feedback controller together with the steady state current for the active magnetic levitation system. Closed-loop dynamics was calculated precisely with respect to the requested dynamics. Two cases were considered: fixed-and variable-closed-loop dynamics. The Fuzzy Logic Controller was considered under four scenarios with linear, nonlinear, and constant in-range output. The study was supported by simulations and experimental investigations. The position of the levitating sphere stands as an illustration of the system in operation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Dynamics

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Scanning the Issue

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IEEE Transactions on Intelligent Transportation Systems 2025年第1期26卷 3-21页

作者： Simona Sacone Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

“Scanning the Issue.“

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Cost-Effective Federated Learning-Based Approach for SINR Prediction in Cellular-Connected UAVs

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Journal of Communications and Information Networks 2025年第4期9卷 374-389页

作者： Mouhamad, Ibrahem Jayakody, Dushantha Nalin K. Vukobratovic, Dejan School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk634050 Russia COPELABS Lusófona University Lisbon1749-024 Portugal Faculty of Technical Sciences University of Novi Sad Novi Sad21000 Serbia

This study introduces a novel approach to empower cellular-connected unmanned aerial vehi-cles (UAVs) in predicting signal quality. The proposed prediction model leverages data collected by the UAVs, addressing privacy concerns and ensuring effectiveness, while taking into account the constraints of UAVs. A unique three-step approach is proposed, which integrates a detailed physical ray-tracing (RT) method, deep learn-ing, and federated learning (FL) for continuous learning and field adaptation. A dual input feature fusion convo-lutional neural network (DIFF-CNN) model is proposed, which is pretrained on RT data and fine-tuned using data collected by the UAVs via FL. The proposed model demonstrates superior performance and robustness to data sparsity compared to traditional machine learning algorithms. Notably, the model achieves a root mean squared error of 0.837 dB and an R-squared of 97.7% for signal-to-interference-plus-noise ratio (SINR) prediction after the fine-tuning step in the fixed-altitude scenario, but performance drops with uniform altitude distribution, highlighting the impact of flying height on fine-tuning. The research indicates that the proposed approach can enhance performance while reducing training rounds by 35% to 90%, thus mitigating FL overheads. Future research could explore efficiency gains by using different pretrained models tailored to specific flying heights. © 2025, Posts and Telecom Press Co Ltd. All rights reserved.

关键词： Mean square error

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Dynamic Subgoal Based Path Formation and Task Allocation: A NeuroFleets Approach to Scalable Swarm robotics

Dynamic Subgoal Based Path Formation and Task Allocation: A ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Peter, Robinroy Ratnabala, Lavanya Andrew Charles, Eugene Yugarajah Tsetserukou, Dzmitry Ltd Jaffna Sri Lanka Skolkovo Institute of Science and Technology Intelligent Space Robotics Laboratory Moscow121205 Russia University of Jaffna Department of Computer Science Jaffna Sri Lanka

ISBN: (纸本)9781665410205

This paper addresses the challenges of exploration and navigation in unknown environments from the perspective of evolutionary swarm robotics. A key focus is on path formation, which is essential for enabling cooperative swarm robots to navigate effectively. We designed the task allocation and path formation process based on a finite state machine, ensuring systematic decision-making and efficient state transitions. The approach is decentralized, allowing each robot to make decisions independently based on local information, which enhances scalability and robustness. We present a novel subgoal-based path formation method that establishes paths between locations by leveraging visually connected subgoals. Simulation experiments conducted in the Argos simulator show that this method successfully forms paths in the majority of trials. However, inter-collision (traffic) among numerous robots during path formation can negatively impact performance. To address this issue, we propose a task allocation strategy that uses local communication protocols and light signal-based communication to manage robot deployment. This strategy assesses the distance between points and determines the optimal number of robots needed for the path formation task, thereby reducing unnecessary exploration and traffic congestion. The performance of both the subgoal-based path formation method and the task allocation strategy is evaluated by comparing the path length, time, and resource usage against the A ∗ algorithm. Simulation results demonstrate the effectiveness of our approach, highlighting its scalability, robustness, and fault tolerance. © 2024 IEEE.

关键词： Traffic congestion

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TFENet: Topological Feature Extraction Network for 6D Object Pose Estimation

TFENet: Topological Feature Extraction Network for 6D Object...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Zhihao Li, Zhengrong Lin, Jiacheng Li, Zhiyong Chen, Wenrui College of Computer Science and Electronic Engineering Hunan University Changsha China School of Robotics Hunan University Changsha China

ISBN: (纸本)9798350303759

Grasping is an essential and challenging skill for robots to interact with their environment. Accurately obtaining the 6D pose information of the grasped object is the key to successful grasping. Due to the influence of illumination changes and object textures, the previous methods had problems with low utilization of depth information and inaccurate feature information. We study feature information extraction and fusion to address these issues and proposed a topological feature extraction network (TFENet). Firstly, we design TFE module to achieve global feature extraction from object point clouds, through which features can be identified to use depth information efficiently. Secondly, we design a MFF module to fuse color and geometric embedding better. Finally, experiments show that the proposed method outperforms existing methods with two datasets, LineMOD and YCB-Video. © 2023 IEEE.

关键词： Feature extraction

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