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Iberian robotics Conference (ROBOT)

作者： Rita Tomé Silva Marina Brilhante Héber Sobreira Diogo Matos Pedro Costa Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto Portugal Centre of Robotics in Industry and Intelligent Systems INESC TEC Porto Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs) have emerged as key innovations in the industry world, with AMRs offering flexibility a nd adaptability for dynamic environments, while AGVs provide high accuracy for repetitive tasks; thus, this research proposes a study of fleets of both AGVs and AMRs to enhance productivity and efficiency in industrial settings. Several tests were performed where the duration of a mission, the success and collision rate, and the average number of disputes per mission were analyzed in order to obtain results. In conclusion, while AGVs tend to be more reliable and consistent in task completion, AMRs offer greater flexibility a nd speed.

关键词： Productivity Technological innovation Remotely guided vehicles Navigation Scalability Path planning Mobile robots Reliability Vehicle dynamics Autonomous robots

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Operational strategies for a photovoltaic-thermal system integrated with an electric air-to-water heat pump 3

Operational strategies for a photovoltaic-thermal system int...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Russo, Giuseppe Olympios, Andreas V. Pandey, Chandan Buonomano, Annamaria Markides, Christos N. University of Naples Federico II Department of Industrial Engineering Naples80125 Italy Laboratory Sargent Centre for Process Systems Engineering Department of Chemical Engineering London United Kingdom University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (纸本)9798350375923

In this study, operational strategies are investigated for an air-based photovoltaic-thermal (PV-T) system integrated with a domestic air-to-water heat pump. The PV-T system is used to simultaneously generate electricity and heat ambient air, which serves as the heat source for the heat pump. By utilising a variable-speed fan to regulate airflow, the PV-T system outlet temperature is adjusted, and the focus is on how different outlet temperatures impact the PVT system electrical and thermal efficiency, heat pump performance, and overall electricity requirements for heating. The performance of the integrated system is assessed for a case study of a household application in north Italy. The optimal PV-T outlet temperature is found to be between 30 - 35 °C, resulting in only 5% less electricity production than an equivalent PV system with equal nominal electricity capacity, while reducing overall electricity required for heating by over 15% compared to PV-integrated heat pumps. © 2024 IEEE.

关键词： Photovoltaics

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Protein-Folding Inspired Programmable Control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhang, Feng Gu, Yuping Wang, Zebin Yuan, Shuai Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China

ISBN: (纸本)9781665481090

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem. © 2024 IEEE.

关键词： Robot programming

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Enhancement of Two-Photon Fluorescence Microscopy Through Auxiliary Microspheres for Microscopic Observation 14

Enhancement of Two-Photon Fluorescence Microscopy Through Au...

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14th IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems, CYBER 2024

作者： Zhang, Feng Jin, Zijian Jiang, Chaodi Yuan, Shuai Yang, Yongliang Wang, Xiaoduo School of Electrical & Control Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798331506056

At present, it is still a great challenge to improve the observation accuracy of two-photon fluorescence microscope. A new method that using auxiliary microspheres as movable components on the sample is proposed to solve this challenge in this study, it can improve high-resolution imaging. In experiments using two-photon fluorescence microscopy, the half-width height (FWHM) of red fluorescent nanoparticles with a diameter of 20 nm was observed to be 296 nm using a primitive microscope system. In this paper by combining barium titanate microspheres with two-photon fluorescence microscopy, the accuracy of the point spread function of the nanoparticles can be improved by a factor of about 1.65, which results in a significant reduction of their half-width height measurements to 179 nm. The research is of great significance to improve the resolution of two-photon fluorescence microscope. This progress is very valuable for studying biological tissues and cell structures, it provides a new impetus for the sustainable development in the microscopic imaging field. © 2024 IEEE.

关键词： Microspheres

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Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions

Magnetic Flux Servoing for Precise Localization Based on Gra...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Dean Martinović Matko Orsag Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

This paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. The hardware involved is presented including the control strategy for the robot. The motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality.

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Correction to: Improving time and energy efficiency in multi-UAV coverage operations by optimizing the UAVs’ initial positions (International Journal of intelligent robotics and Applications, (2024), 10.1007/s41315-024-00333-2)

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International Journal of intelligent robotics and Applications 2024年第1期9卷 365-373页

作者： Stefanopoulou, Aliki Raptis, Emmanuel K. Apostolidis, Savvas D. Gkelios, Socratis Kapoutsis, Athanasios Ch. Chatzichristofis, Savvas A. Vrochidis, Stefanos Kosmatopoulos, Elias B. Information Technologies Institute The Centre for Research & ampTechnology Hellas 6th km Harilaou - Thermis Thessaloniki57001 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Kimmeria Campus Xanthi67100 Greece Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos 2 Danais Avenue PafosCY 8042 Cyprus

In the original publication, the author has found few errors in the figures 2, 4, 11 and 12 which significantly impact both the paper's quality and the reputation of the journal. These issues undermine the clarity of the methodology and the novelty of the research. 1. Each column represents a different case in the experiment, corresponding to the number of UAVs in both the obstacle-free and obstacle areas. However, in Fig. 2, the first row contains identical subfigures across all columns, while the subfigures in the remaining rows are identical to each other The incorrect Fig. 2 appears as below: (Figure presented.) However the corrected Fig. 2 should appear as below. (Figure presented.) 2. In Fig. 4, every row showcase the average QoF for the testing scenarios (obstacle-free and obstacle area). However the first row has the exact same figures with the second row. The incorrect Fig. 4 appears as below: (Figure presented.) However the corrected Fig. 4 should appear as below. (Figure presented.) 3. Figures 11 and 12 showcase the distribution of each Quality of Flight (QoF) metric value for every UAV in the conducted trials during the testing scenarios. However, Fig. 11 is the same with Fig. 12. The incorrect Figs. 11 and 12 appears as below: (Figure presented.) However the corrected Figs. 11 and 12 should appear as below. (Figure presented.) Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle-free area Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle area The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

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Inverse Kinematics of Robotic Manipulators Using a New Learning-by-Example Method

Inverse Kinematics of Robotic Manipulators Using a New Learn...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Jacket Demby’s Ramy Farag Guilherme N. DeSouza Department of Electrical Engineering and Computer Science (EECS) Vision-Guided and Intelligent Robotics (ViGIR) Laboratory University of Missouri-Columbia Columbia Missouri

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Inverse Kinematics (IK) is one of the most fundamental challenges in robotics. It refers to the process of determining the joint configurations required to achieve the desired position and orientation (pose) of a robot end-effector. Although numerous Data-Driven (DD) IK solvers have demonstrated encouraging results, they have not achieved the same accuracy when compared to other IK methods for complex robot configurations (e.g., numerical methods for higher Degrees of Freedom (DoF)). In this work, we propose a new Learning-by-Example method, and show that such a scheme considerably improves the IK learning results when compared to other DD learners. In our approach, the network input incorporates an example of joint-pose pair along with the query pose to predict the desired robot joint configuration. We show that the example joint-pose pair does not need to be too close to the query – i.e. example and query can be as far as 20 degrees apart in the joint configuration space. Furthermore, we investigate the utilization of residual and dense skip connections in Multilayer Perceptron for DDIK solvers and employ the resulting networks for two redundant robotic manipulators: a 7-DoF-7R commensurate robot and a 7DoF-2RP4R incommensurate robot. Our experimental results show that the resulting DDIK solver can reliably predict IK solutions with accuracy better than 1mm in position and 1deg in orientation.

关键词： Hands Accuracy Kinematics Network architecture Multilayer perceptrons Numerical models Reliability Collision avoidance Robots intelligent robots

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Graph Models of Electric Power Transmission Networks Using Synchrophasor Data

Graph Models of Electric Power Transmission Networks Using S...

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IEEE Southeastcon

作者： Ganesh K. Venayagamoorthy Dulip Madurasinghe Rajan Ratnakumar Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University SC USA

The electric power transmission network (EPTN) is a connected, geographically distributed network, which can be represented with a graph model with nodes and edges. The graph represents the physical connectivity of the EPTN. Deriving the graph model of the EPTN solely based on continually measured data is important for reliable power system operational situation awareness and decreasing uncertainties driven by weather, electrification, and interconnections. In this paper, an exhaustive search algorithm is presented to derive the EPTN graph model (TNGM) solely based on synchrophasor measurements retrieved from the substations without prior knowledge of the connectivity. Furthermore, an evaluation metric for any data-driven TNGM is introduced. The transmission network of the two-area, four-machine power system is used as the test system, and typical TNGMs for different power plant operating conditions are presented. Typical graphs obtained for network impedance and power flows are shown to be accurate, on average within 2% error margin.

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Online Prediction of Novel Trajectories Using a Library of Movement Primitives

Online Prediction of Novel Trajectories Using a Library of M...

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IEEE International Conference on Development and Learning, ICDL

作者： Paris Oikonomou Athanasios Dometios Mehdi Khamassi Costas S. Tzafestas School of Electrical and Computer Engineering National Technical University of Athens Greece Sorbonne Université CNRS Institute of Intelligent Systems and Robotics Paris France

ISBN: (数字)9798350348552

ISBN: (纸本)9798350348569

Learning to anticipate other agents' future movements has gained increased interest in robotics, especially in situations requiring interaction. Such a prediction allows the robotic systems to plan their actions as a task evolves and before its completion. Specifically, in case of active robot collaboration, early decision making might ensure smoothness during motion and collision avoidance. While previous work has addressed prediction and recognition of primitive actions, to our knowledge little attention has been paid to the aspect of unseen ones. In this paper, we introduce a method for online continuous prediction of the evolution of previously unseen trajectories based on a recency weighting of past observations using a library of trained probabilistic movement primitives (ProMPs). The proposed method makes the assumption that parts of any novel trajectory could be considered as a combination of simpler ones. A probability distribution is derived across the evolution of the trajectory, and is updated in a recursive manner. We present a set of simulation experiments to showcase the new method, and compare it with a state-of-the-art method.

关键词： Decision making Collaboration Probabilistic logic Libraries Probability distribution Trajectory Collision avoidance

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DORAC: Dynamic-Objects Removal and Clustering for Object Detection

DORAC: Dynamic-Objects Removal and Clustering for Object Det...

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Cyber Science and Technology Congress (CyberSciTech), IEEE

作者： Kwanho Kiml Dokyung Kim Kanghyun Jo Dept. of Electrical Electronic and Computer Engineering (University of Ulsan) Intelligent Systems Laboratory Ulsan Republic of Korea

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

Object detection using deep learning approach is being utilized for many fields such as autonomous driving, traffic analysis, etc. However, deep learning approach shows some fundamental limitations related to collecting datasets or explainabilty caused by its unclearness of the process for reaching a specific conclusion. This paper proposes DORAC which refers to Dynamic-Objects Removal And Clustering for object detection and does not use any deep neural networks. DORAC can be operated at videos captured by fixed camera. Frames of a video are averaged for removing dynamic objects. Then, the confidence map obtained from subtraction between video frame and averaged image is processed by thresholding and clustering. Experiments show that proposed method outperforms the state-of-the-art deep learning models trained with remarkable dataset by over 5% for our industry videos. In addition to metrics related to accuracy, frame rate of the method proposed in this paper is also 0.5 frames faster than YOLOv9-tiny model in CPU, averagely.

关键词： Deep learning Measurement Industries Accuracy Object detection Artificial neural networks Cameras Autonomous vehicles Videos

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