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检索条件"机构=Robotics and Intelligent Systems Laboratory Electrical and Computer Engineering"

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Exploring the Integration of Educational robotics and the Internet of Things in Learning Environments

Exploring the Integration of Educational Robotics and the In...

引用

International Conference on Distributed Computing in Sensor systems (DCOSS)

作者： Elena Kakoulli Salomi Evripidou Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

This study explores the integration of Educational robotics (ER) and the Internet of Things (IoT) in learning environments, highlighting their collective impact on educational practices. It assesses ER and IoT’s application, challenges, and opportunities, offering insights into their role in enhancing pedagogy and learning outcomes. Specifically, our exploration uncovers the transformative potential of ER and IoT in fostering critical thinking, problem-solving skills, and digital literacy among students and reveals the pivotal role these technologies play in preparing learners for the demands of the digital age and Industry 4.0, while also highlighting the need for strategic implementation and teacher support. Our findings elucidate the potential of ER and IoT to innovate teaching strategies and curriculum design, serving as a guide for educational stakeholders, such as curriculum developers, educators, researchers, and policymakers, in leveraging these technologies to revolutionize instructional practices.

关键词： Training Information age Fourth Industrial Revolution Internet of Things Stakeholders Problem-solving Distributed computing

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IRS/UAV-Based Edge-Computing and Traffic-Offioading Over 6G THz Mobile Wireless Networks

IRS/UAV-Based Edge-Computing and Traffic-Offioading Over 6G ...

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2023 IEEE International Conference on Communications, ICC 2023

作者： Wang, Fei Zhang, Xi Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas A&m University College StationTX77843 United States

ISBN: (纸本)9781538674628

intelligent reflecting surface (IRS), unmanned aerial vehicle (UAV), and Terahertz (THz) communications, which are recognized as 6G promising techniques, have attracted significant attentions. We propose UAV energy minimization schemes for IRS/UAV-based mobile-edge-computing (MEC) and traffic-offloading over broadband THz mobile networks. In the networks, multiple UAVs serving as MEC-servers collect data from multiple ground users (GUs) with the assistance of a set of passive IRSs. First, we formulate a UAV energy minimization problem, which jointly optimizes the IRSs' phase shifts, UAVs' trajectories, and system computation and communication resources. For THz communications, since the composite channel power gains of GUs are complicated functions of UAVs' trajectories and IRSs' phase shifts, the formulated optimization problem is non-convex. Then, using the alternating optimization (AO) technique, we decompose this non-convex optimization problem into three sub-problems which then can be iteratively solved. Finally, we validate and evaluate the proposed schemes by numerical analyses, which show that the energy consumption of UAVs can be reduced by around 40% by using IRSs. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Skeleton-based Action Recognition Using Two-stream Graph Convolutional Network with Pose Refinement 41

Skeleton-based Action Recognition Using Two-stream Graph Con...

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第41届中国控制会议

作者： Biao Zheng Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.

关键词： Graph convolutional network Pose refinement Skeleton based action recognition Adaptive block

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Accurate Parameter Estimation for PMSMs using electrical and Mechanical Models Considering Temperature Effect and Inverter Distortion

Accurate Parameter Estimation for PMSMs using Electrical and...

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2022 Chinese Automation Congress, CAC 2022

作者： Tong, Zhe Meng, Bo Ding, Beichen Feng, Guodong Lai, Chunyan Sun Yat-sen University School of Intelligent Systems Engineering Shenzhen China Sun Yat-sen University School of Intelligent Systems Engineering Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology Guangzhou510006 China Concordia University Department of Electrical and Computer Engineering Montreal Canada

ISBN: (纸本)9781665465335

This paper presents a decoupled parameter estimation method for PMSM considering temperature rise and inverter distortion. Both electrical and mechanical models are explored to derive the estimation model to achieve better parameter estimation accuracy. Specifically, the proposed approach firstly performs the initial estimation of the PM flux, winding resistance and friction coefficient by considering the temperature effect, and then derives the decoupled model for inductance estimation using both the electrical and mechanical measurements. Compared with other approaches, our decoupled approach employs the mechanical model and considers the temperature effect, which can make the parameter identification more accurate. The experiment is performed on a test PMSM to verify the estimation performance of the proposed approach. © 2022 IEEE.

关键词： Parameter estimation

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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FEIF: Feature Excitation and Interactive Fusion for 6D Object Pose Estimation

FEIF: Feature Excitation and Interactive Fusion for 6D Objec...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Meng, Qiwei Zhu, Shiqiang Gu, Jianjun Lin, Zheyuan Zhong, Ling Song, Wei Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

In this paper, we present FEIF, a novel framework for 6D object pose estimation from a single RGBD image. Compared with previous approaches, this model fully leverages the complementary RGB and depth information through lay-erwise feature excitation and interactive fusion, thus improving the effectiveness and robustness of extracted features. The representative RGBD features can be subsequently applied for object keypoints prediction and pose computation. In addition, our FEIF includes a self-evaluation module to make robots aware of the confidence of pose estimation, so they are flexible to take the corresponding strategy for following tasks. Experiment results prove the SOTA performance of our model on LineMOD, Occlusion-LineMOD and YCB-Video datasets, and we also demonstrate its applicability and robustness in real-world robotic manipulation. © 2022 IEEE.

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Power Dispatch Estimation from Electric Vehicles in a Distribution System

Power Dispatch Estimation from Electric Vehicles in a Distri...

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International Conference on Electric Power and Energy Conversion systems (EPECS)

作者： Ganesh K. Venayagamoorthy Imanthi Kalanika Subasinghe Raj Naidoo Holcombe Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson SC USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

The integration of electric vehicles (EVs) into the electric power distribution system poses numerous challenges and opportunities for optimizing energy management and system operations. Electric vehicle grid interfaces (EVGIs), essentially bidirectional power converters, allow for charging/grid-to-vehicle (G2V) and discharging/vehicle-to-grid (V2G) power transfers. A power dispatch estimation (PDE) model for V2G, based on availability of EVs in a distribution system and capabilities of the distribution system, is needed to assist in grid operations. This paper presents the development of a PDE model based on nodal power flows to capture the complex spatiotemporal dependencies inherent in G2V and V2G patterns. The hierarchical structure of a distribution system, feeder to EVGI node, is taken into consideration for PDE. Typical PDE estimation results are presented for the IEEE 34 test node feeder distribution system allocated with EVGIs.

关键词： Partial discharges Vehicle-to-grid systems operation Estimation Spatiotemporal phenomena Resource management Energy management Voltage control Vehicle dynamics Sustainable development

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HSMR: A Head-Shoulder Mask Aided ResNet to Guide Focus of Re-Identification Implemented on Tour-Guide Robot

HSMR: A Head-Shoulder Mask Aided ResNet to Guide Focus of Re...

引用

2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Lin, Zheyuan Huang, Min Wang, Wen Qin, Mengjie Li, Te Wan, Minhong Gu, Jason Zhu, Shiqiang Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

For service robots, person re-identification (ReID) and multi-pedestrian tracking (MPT) are vital to get a person's location and link identities across frames. Though their accuracy keeps improving, most work lacks consideration of the application scenario, haunted by limited space, constrained power supply, and demands of the real-time response during human-robot interaction. Some ReID models learn trivial or unrelated features, inhibiting the downstream tasks. To solve these issues, the efficient and light-weighted Head-Shoulder Mask aided ResNet (HSMR) is proposed. This model applies multi-task learning to enhance the feature extraction performance in the training stage without extra computational load during inference. The auxiliary task fully uses head-shoulder information to guide the network and focuses on the head region, which contains the identity information. In experiments on the Tour-Guide Robot Data Base (TGRDB), HSMR earned results better than ResNet-18 on the ReID task and was superior to the recent two-stream method on the MPT task. On the mobile hardware, inference reaches an average of 15.2 FPS, three times faster than the two-stream method. The code is released at https://***/ZhYLin99/HSMR. © 2022 IEEE.

关键词： Human robot interaction

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Low-cost Mars Terrain Classification System Based on Coarse-grained Annotation

Low-cost Mars Terrain Classification System Based on Coarse-...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhang, Jian Chen, Yeheng Zhu, Shiqiang Li, Yuehua Xie, Tian Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

Due to communication latency with remote ground sites, automatic recognition of Mars terrain is essential for the path-planning of rovers. Currently, most vision-based terrain classification require thousands of fine-grained training samples, while the undefined terrains on Mars are difficult to be classified or fine-grained labeled. Actually, most of the terrain categories can only be coarse-grained labeled due to several limitations, such as overlapped sub-regions, blurred borders, etc. To solve this problem, CACMT (Coarse-grained Annotation-based Classification for Mars Terrain) is proposed to generate the global fine-grained classification map from the local coarse-grained data. Specifically, the complete pipeline is decomposed into (i) annotation rules with unique design, (ii) hierarchical feature fusion network for predicting sub-features of terrain (iii) and a generator for outputting dense terrain categories of Mars. Finally, the results of actual data on Mars demonstrate that the terrain sub-features can be successfully recognized and a dense terrain classification map can be generated applying only coarse-grained labeled images. © 2022 IEEE.

关键词： Motion planning

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Robust Control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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