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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： S M Sajjad Hossain Rafin Qasim Ali Fei Zhao Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798350362213

ISBN: (纸本)9798350362220

A novel three-layer sub-harmonic synchronous machine is proposed, equipped with consequent permanent magnets and windings for superior torque generation and better overall performance. The consequent pole PM rotor design reduces the PM quantity by half versus conventional configurations without compromising performance. Finite element analysis of an 8-pole, 48-slot machine verifies a 6% increase in torque generation and 4 % lower torque ripple compared to a fully PM -assisted design. The proposed machine also outperforms alternatives on metrics, including torque density and efficiency. These favorable characteristics demonstrate the promise of the topology as a cost-effective, high-performing electric propulsion candidate. This work contributes to an innovative machine advancing progress toward affordable PM -assisted synchronous motors.

关键词： Measurement Torque Windings Rotors Magnetic devices Production Propulsion

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Visual numerical cognition in pigeons: conformity to the Weber–Fechner law

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Animal Cognition 2025年第1期28.0卷 1-13页

作者： Wu, Peng Zhu, Juncai He, Qingzhi Wang, Zhizhong Shi, Li School of Electrical and Information Engineering Zhengzhou University Zhengzhou 450001 China Department of Automation Tsinghua University Beijing 100084 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou 450001 China

As representatives of a basal bird lineage, pigeons have exhibited remarkable visual numerical cognition, comparable even to that of monkeys. Nevertheless, whether visual numerical cognition in pigeons conforms to the Weber–Fechner law remains unknown. To address this, we designed a fully automated apparatus tailored for pigeons and used it to train them to perform a delayed match-to-numerosity task. The results showed that on a linear scale, pigeons represented smaller numerosities with higher precision and larger numerosities with lower precision, exhibiting a numerical magnitude effect. When the linear scale was compressed into a logarithmic scale, this magnitude effect was offset, resulting in similar representational characteristics across different numerosities. This finding suggests that the mental number line of pigeons is logarithmic rather than linear, consistent with the Weber–Fechner law. While biological brains seek precision in representing numerical information, they must also take computational load into account. This representational strategy may be the optimal outcome of the trade-off between computational precision and computational load that biological brains have achieved through long-term evolution. © The Author(s) 2025.

关键词： Birds Logarithm Mental number line Numerosity Pigeons

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ACO-GA-Based Optimization to Enhance Global Path Planning for Autonomous Navigation in Grid Environments

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IEEE Transactions on Evolutionary Computation 2025年

作者： Heng, Han Rahiman, Wan Universiti Sains Malaysia Engineering Campus School of Electrical and Electronic Engineering Penang14300 Malaysia Universiti Sains Malaysia Engineering Campus Nibong Tebal Penang14300 Malaysia Daffodil Robotics Laboratory Department of Computer Science and Engineering Daffodil International University Dhaka1216 Bangladesh

Exploring path planning techniques for autonomous vehicles to find the safest and quickest routes is fascinating. Among these techniques, generating grid-based maps is notable for simplifying the path planning process, especially in complex environments. This study introduces a novel optimization approach, the modified ant colony optimization and genetic algorithm (MACOGA), which is tailored for path planning in grid environments. MACOGA combines ant colony optimization (ACO) with genetic algorithm (GA) to efficiently navigate grid spaces. First, ACO identifies potential routes within a grid map, and GA optimizes them to find the optimal route. A key feature of MACOGA is its probabilistic prediction mechanism, which improves node selection by integrating the heuristic factors and probabilistic calculations of feasible potential paths, which significantly increases the likelihood of generating feasible initial paths and attains higher success rates in various environmental tests. The enhanced GA in the MACOGA incorporates ACO's pheromones and heuristic factors, and introduces adaptive probability crossover and mutation operations. Additionally, a path reconnection operation ensures favorable length and smoothness. To evaluate MACOGA's effectiveness, six planar models of varying sizes and complexities were studied. Results show MACOGA's superiority in path length and execution time, achieving the shortest path and planning time in several environments. The shortest path can be optimized to yield an improvement of up to 6%. Regarding runtime, even in the complex scenarios, it executes in just 0.3 seconds, outperforming other comparative algorithms. Furthermore, the success rate can reach 100% in relatively complex environments. © 2025 IEEE.

关键词： Ant colony optimization

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Motion Prediction Based on sEMG- Transformer for Lower Limb Exoskeleton Robot Control 8

Motion Prediction Based on sEMG- Transformer for Lower Limb ...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Zeng, Min Gu, Jason Feng, Ying Anhui University Institute of Artificial Intelligence Hefei Comprehensive National Science Center AHU-IAI AI Joint Laboratory Hefei230601 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada College of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

While lower limb exoskeleton robots can realize assisted walking by extracting the user's motion intention, it is difficult to effectively obtain the motion intention of the human body and convert it into information for the robot. In this paper, a novel model based on sEMG-Transformer is proposed for continuous motion prediction of multiple joint angles of lower limbs and applied to the developed lower limb exoskeleton robot. The sEMG-Transformer model can be used to extract the time series features from the sEMG sequences and establish the mapping between input data and multi-joint angle. Then, the predicted multi-joint angles are inputted into the developed lower limb exoskeleton robot. Experimental studies are performed with able-bodied human wearers and compared to existing methods, such as convolutional neural network (CNN), back propagation (BP), and long short-term memory (LSTM) networks. The motion intention estimation based on the sEMG-Transformer network has better estimation performance, which can effectively enable users to walk synchronously with the lower limb exoskeleton robot. © 2023 IEEE.

关键词： Backpropagation

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Optimal Placement of Voltage Regulator and Capacitor for Distribution System

Optimal Placement of Voltage Regulator and Capacitor for Dis...

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2021 International Conference on System, Computation, automation and Networking, ICSCAN 2021

作者： Rajalakshmi, M. Addisu, Molla Jeyakkannan, N. Renuka Devi, G. Karthik, C. Jyothi Engineering College Department of Mechatronics Thrissur India Woldia University Department of Electrical and Computer Engineering Ethiopia Manakula Vinayagar Institute of Technology Deprtment of Robotics and Automation Puduchery India

ISBN: (纸本)9781665439862

The radial distribution system (RDS) is the ultimate link between the high-voltage transmission system (HVT) and the user in most electrical systems in Ethiopia. The Distribution System (DS) is divided into different areas for proper operation and supply of electricity demand. The study in this paper applies specifically to the Gondar feeder, which consists of 60 nodes with 3,413 MW of total capacity, in power distribution lines. For the modulation of voltages and DS node power loss indices, the fuzzy membership functions are used. A fluid expert system (FES) with a collection of heuristic legislation will determine the voltage regulator and the capacitor suitability index. The proposed method discusses and compares the effectiveness and results obtained from the voltage control system and the optimal placement of capacitors. © 2021 IEEE.

关键词： Voltage regulators

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Design of A Third-order Inline Waveguide Bandpass Filter With Cross Coupling and Spurious Mode Suppression

Design of A Third-order Inline Waveguide Bandpass Filter Wit...

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IEEE International Wireless Symposium (IWS)

作者： Wangtao Ye Zai-Cheng Guo Lei Zhu Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing School of Electrical and Automation Engineering Nanjing Normal University Nanjing Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (数字)9798350389999

ISBN: (纸本)9798350390001

A third-order inline waveguide bandpass filter (BPF) with cross coupling and spurious mode suppression is designed in this paper. Based on the conventional cascaded-coupled filter, the cross coupling is realized by reducing the height of the second resonating cavity and introducing a stacked cavity for cross coupling, which generates a transmission zero (TZ) on the right side of passband. In order to eliminate the spurious modes caused by the cross-coupled cavity, a short-circuited post is introduced to make TE101 and TE102 mode of the cavity introduced for cross coupling self-suppressed. Therefore, the proposed inline waveguide BPF is with one TZ on the right side of passband while preserving almost the same bandwidth of stopband when compared to the conventional cascaded-coupled filter. The design process is illustrated in detail and the measured results verify the feasibility of the proposed inline waveguide BPF.

关键词： Band-pass filters Couplings Wireless communication Bandwidth Filtering theory Passband

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Efficient Object Rearrangement via Multi-view Fusion

Efficient Object Rearrangement via Multi-view Fusion

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IEEE International Conference on robotics and automation (ICRA)

作者： Dehao Huang Chao Tang Hong Zhang Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The prospect of assistive robots aiding in object organization has always been compelling. In an image-goal setting, the robot rearranges the current scene to match the single image captured from the goal scene. The key to an image-goal rearrangement system is estimating the desired placement pose of each object based on the single goal image and observations from the current scene. In order to establish sufficient associations for accurate estimation, the system should observe an object from a viewpoint similar to that in the goal image. Existing image-goal rearrangement systems, due to their reliance on a fixed viewpoint for perception, often require redundant manipulations to randomly adjust an object’s pose for a better perspective. Addressing this inefficiency, we introduce a novel object rearrangement system that employs multi-view fusion. By observing the current scene from multiple viewpoints before manipulating objects, our approach can estimate a more accurate pose without redundant manipulation times. A standard visual localization pipeline at the object level is developed to capitalize on the advantages of multi-view observations. Simulation results demonstrate that the efficiency of our system outperforms existing single-view systems. The effectiveness of our system is further validated in a physical experiment. For videos, please visit https: //***/view/multi-view-rearr.

关键词： Visualization Accuracy Databases Simulation Standards organizations Pose estimation Pipelines

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Optimizing NeRF-based SLAM with Trajectory Smoothness Constraints

arXiv

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arXiv 2024年

作者： He, Yicheng Chen, Guangcheng Zhang, Hong Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

The joint optimization of Neural Radiance Fields (NeRF) and camera trajectories has been widely applied in SLAM tasks due to its superior dense mapping quality and consistency. NeRF-based SLAM learns camera poses using constraints by implicit map representation. A widely observed phenomenon that results from the constraints of this form is jerky and physically unrealistic estimated camera motion, which in turn affects the map quality. To address this deficiency of current NeRF-based SLAM, we propose in this paper TS-SLAM (TS for Trajectory Smoothness). It introduces smoothness constraints on camera trajectories by representing them with uniform cubic B-splines with continuous acceleration that guarantees smooth camera motion. Benefiting from the differentiability and local control properties of B-splines, TS-SLAM can incrementally learn the control points end-to-end using a sliding window paradigm. Additionally, we regularize camera trajectories by exploiting the dynamics prior to further smooth trajectories. Experimental results demonstrate that TS-SLAM achieves superior trajectory accuracy and improves mapping quality versus NeRF-based SLAM that does not employ the above smoothness constraints. © 2024, CC BY.

关键词： Mapping

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RTAGrasp: Learning Task-Oriented Grasping from Human Videos via Retrieval, Transfer, and Alignment

arXiv

引用

arXiv 2024年

作者： Dong, Wenlong Huang, Dehao Liu, Jiangshan Tang, Chao Zhang, Hong Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

Task-oriented grasping (TOG) is crucial for robots to accomplish manipulation tasks, requiring the determination of TOG positions and directions. Existing methods either rely on costly manual TOG annotations or only extract coarse grasping positions or regions from human demonstrations, limiting their practicality in real-world applications. To address these limitations, we introduce RTAGrasp, a Retrieval, Transfer, and Alignment framework inspired by human grasping strategies. Specifically, our approach first effortlessly constructs a robot memory from human grasping demonstration videos, extracting both TOG position and direction constraints. Then, given a task instruction and a visual observation of the target object, RTAGrasp retrieves the most similar human grasping experience from its memory and leverages semantic matching capabilities of vision foundation models to transfer the TOG constraints to the target object in a training-free manner. Finally, RTAGrasp aligns the transferred TOG constraints with the robot’s action for execution. Evaluations on the public TOG benchmark, TaskGrasp dataset, show the competitive performance of RTAGrasp on both seen and unseen object categories compared to existing baseline methods. Real-world experiments further validate its effectiveness on a robotic arm. Our code, appendix, and video are available at https: //***/view/rtagrasp/home. © 2024, CC BY.

关键词： Robotic arms

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An Enhanced Data-Driven Model for Lithium-Ion Battery State-of-Health Estimation with Optimized Features and Prior Knowledge

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Automotive Innovation 2022年第2期5卷 134-145页

作者： Huanyang Huang Jinhao Meng Yuhong Wang Lei Cai Jichang Peng Ji Wu Qian Xiao Tianqi Liu Remus Teodorescu College of Electrical Engineering Sichuan UniversityChengduChina Faculty of Computer Science and Engineering Shanxi Key Laboratory for Network Computing and Security TechnologyXi’an University of TechnologyXi’anChina Smart Grid Research Institute Nanjing Institute of TechnologyNanjingChina Department of Automation University of Science and Technology of ChinaHefeiChina Key Laboratory of Smart Grid of Ministry of Education Tianjin UniversityTianjinChina Department of Energy Technology Aalborg University9220 AalborgDenmark

In the long-term prediction of battery degradation,the data-driven method has great potential with historical data recorded by the battery management *** paper proposes an enhanced data-driven model for Lithium-ion(Li-ion)battery state of health(SOH)estimation with a superior modeling procedure and optimized *** Gaussian process regression(GPR)method is adopted to establish the data-driven estimator,which enables Li-ion battery SOH estimation with the uncertainty level.A novel kernel function,with the prior knowledge of Li-ion battery degradation,is then introduced to improve the mod-eling capability of the *** for the features,a two-stage processing structure is proposed to find a suitable partial charging voltage profile with high *** the first stage,an optimal partial charging voltage is selected by the grid search;while in the second stage,the principal component analysis is conducted to increase both estimation accuracy and computing *** of the proposed method are validated on two datasets from different Li-ion batteries:Compared with other methods,the proposed method can achieve the same accuracy level in the Oxford dataset;while in Maryland dataset,the mean absolute error,the root-mean-squared error,and the maximum error are at least improved by 16.36%,32.43%,and 45.46%,respectively.

关键词： Li-ion battery State of health Gaussian process regression Kernel function Feature optimization

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