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检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

共 24829 条记录，以下是4061-4070 订阅

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Communication-Aware Map Compression for Online Path-Planning

Communication-Aware Map Compression for Online Path-Planning

引用

IEEE international conference on robotics and automation (ICRA)

作者： Evangelos Psomiadis Dipankar Maity Panagiotis Tsiotras D. Guggenheim School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering University of North Carolina at Charlotte NC USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper addresses the problem of the communication of optimally compressed information for mobile robot path-planning. In this context, mobile robots compress their current local maps to assist another robot in reaching a target in an unknown environment. We propose a framework that sequentially selects the optimal level of compression, guided by the robot’s path, by balancing map resolution and communication cost. Our approach is tractable in close-to-real scenarios and does not necessitate prior environment knowledge. We design a novel decoder that leverages compressed information to estimate the unknown environment via convex optimization with linear constraints and an encoder that utilizes the decoder to select the optimal compression. Numerical simulations are conducted both in a large close-to-real map and a maze map and compared with two alternative approaches. The results confirm the effectiveness of our framework in assisting the robot reach its target by reducing transmitted information, on average, by approximately 50%, while maintaining satisfactory performance.

关键词： Costs Simulation Search methods Numerical simulation Convex functions Decoding Mobile robots

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Development of a Method for Approaching the Autonomous Vehicle to a Moving Object

Development of a Method for Approaching the Autonomous Vehic...

引用

international Russian automation conference (RusAutoCon)

作者： Irina Naidanova Anton Gubankov Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Maritime State University Named after Admiral G.I. Nevelskoy Vladivostok Russia Robotics Laboratory Institute of Automation and Control Processes Maritime State University Named after Admiral G.I. Nevelskoy Vladivostok Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The paper considers the development of a method for approaching an autonomous vehicle to a moving object. Approaching to objects may be necessary in various fields, for example, when landing an unmanned aircraft on a moving platform, animals and marine wildlife photo and videorecording, following the leader in group control, etc. It is assumed that the coordinates of the object are obtained without delay, however, at some points in time, position data is not received, that is, the trajectory of the object is represented by several separate segments of the trajectory. The paper proposes to use a combination of two classical guidance methods to approach the object. This eliminates the disadvantages of both methods and increases the overall efficiency of movement to the object. The pursuit method is used at short distances between the controlled vehicle and the object. The proportional approach method is used at long distances. A comparison of the simulation results on the generated data of the developed algorithm with the results obtained using only classical methods confirms the efficiency of simultaneous use of two guidance methods.

关键词： automation Simulation Wildlife Trajectory Delays Kalman filters Aircraft Autonomous vehicles Aerospace control

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Integrating Visual Reasoning Localization with Reinforcement Learning for 3C Assembly

Integrating Visual Reasoning Localization with Reinforcement...

引用

IEEE international conference on robotics and Biomimetics

作者： Baolin Huang Huaidong Zhou Jiaqi Zhang Fuchun Sun Jiahui Guo Department of Computer Science and Technology Tsinghua University Beijing China School of Automation Beijing Information Science and Technology University Beijing China School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In 3C (Computer, Communication, and Consumer Electronics) flexible assembly tasks, due to the frequent updates and the increasing demand for intelligence, traditional automated assembly methods struggle to meet the requirements for high precision and adaptability. To address these challenges, this paper proposes an assembly method that combines visual reasoning localization with deep reinforcement learning. The method improves the reward function by integrating visual reasoning results with reinforcement learning and trains the model in a virtual environment. Through sim-to-real transfer, the assembly strategies learned in the virtual environment are applied to real-world scenarios, significantly enhancing the assembly accuracy and success rate in real-world settings. Validation on a 3C front camera assembly task demonstrates an assembly accuracy of 0.15 mm and a success rate of 97%.

关键词： Location awareness Training Visualization Accuracy Virtual environments Cameras Cognition Assembly Smart phones Testing

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An Innovative Approach to Glass Classification Using Deep Neural Network

An Innovative Approach to Glass Classification Using Deep Ne...

引用

robotics, automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE international conference on

作者： Md Shohanur Rahman Tania Sultana Wahid Tausif Islam Md. Rifat Ahmed Khan Department of CSE Daffodil International University Dhaka Bangladesh Department of CSE American International University Bangladesh Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

A novel method for classifying glasses using deep neural networks is presented. The study uses data from the USA Forensic Science Service to classify six different varieties of glass according to their oxide level. The dataset is carefully cleaned up using preprocessing methods like Min-Max Scaling and Label Encoding to improve data quality and make it more neural network architecture compatible. The deep neural network model performs admirably in this difficult task, correctly categorizing glass samples with an accuracy of 81.40%. The analysis of the results shows that different varieties of glass behave differently, pointing out both areas of strength and improvement. In the future, the work may entail investigating more sophisticated deep learning techniques including transfer learning and attention processes, as well as broadening the dataset to include a greater range of glass samples. Moreover, validation tests conducted in the actual world and the model's implementation in industrial settings may offer important new perspectives on its usefulness. In general, this study advances automated glass categorization methods, which may have consequences for activities related to environmental sustainability, product creation, and quality assurance in a variety of sectors.

关键词： Accuracy Quality assurance Service robots Transfer learning Refining Glass Artificial neural networks Recycling Manufacturing Sustainable development

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An Impedance Spectrum-based Simulation Method for Lithium-ion Batteries 4

An Impedance Spectrum-based Simulation Method for Lithium-io...

引用

4th international conference on Advances in Electrical Engineering and Computer Applications, AEECA 2023

作者： Jian, Zhichao Wen, Haoyong Xie, Yulong Tan, Yongcheng Du, Shihai Yang, Lei Bai, Miao Lyu, Chao No. 1 Substation Management Office of Dongguan Power Supply Bureau of Guangdong Power Grid Co. Ltd Dongguan China Harbin Institute of Technology School of Electrical Engineering and Automation Harbin China

ISBN: (纸本)9798350308082

Lithium-ion batteries have gained significant traction in the energy storage and electric vehicle sectors due to their remarkable attributes such as superior energy density, extended lifespan, and cost-effectiveness. This has made them an appealing choice amidst the energy crisis and the pursuit of carbon peaking and carbon neutrality objectives. Accurate battery simulation methods play important roles in both theoretical research and practical applications of batteries. Currently, most battery simulation methods are based on equivalent circuit models. An impedance spectrum-based simulation method for lithium-ion batteries is presented in this paper. In this method, the fractional-order equivalent circuit model is first developed and the impedance spectrum is used for model parameter identification. Then, the frequency domain model is converted to a time domain model by means of fractional order calculus. Finally, the model is used to perform battery terminal voltage simulations under dynamic working conditions and constant current condition to verify the accuracy of the method. © 2023 IEEE.

关键词： Electrochemical impedance spectroscopy

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Fast and High Precision Surface Defect Detection Method Based on New Label Assignment

Fast and High Precision Surface Defect Detection Method Base...

引用

IEEE international conference on Real-time Computing and robotics (RCAR)

作者： Ruitao Li Xiaojun Wu Jinghui Zhou Jiarui Zheng School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Information Technology and Engineering Taizhou Vocational & Technical College Taizhou China Shenzhen Liande Automation Equipment Co. Ltd Shenzhen China

Current object detection networks suffer from low accuracy and slow speed for industrial defect detection tasks. Industrial defect detection tasks are characterized by small area and large aspect ratio of the detected objects, as well as high speed requirements. We provide a label assignment strategy for defect shape characteristics to improve the training efficiency of a one-stage target detection network for defect detection scenarios. Also, label assignment distillation learning is used to obtain a model that takes into account the speed of detection. In this paper, experiments are conducted on several industrial defect datasets, and metrics such as mAP (mean average precision) values and inference speed are calculated. Compared with other models, the label assignment algorithm results in a 3% improvement in detection accuracy and a 58% acceleration in model inference speed after lightweighting.

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Edge Computing for Real-Time Decision-Making in Industrial automation Systems - A Comprehensive Review

Edge Computing for Real-Time Decision-Making in Industrial A...

引用

Advancements in Electrical, Electronics, Communication, Computing and automation (ICAECA), international conference on

作者： R. Raffik V. J. Balamurugan N. Gopinath Pandian Department of Mechatronics Engineering Kumaraguru College of Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

The real-time decision-making potential brought by edge computing is disrupting industrial automation, transcending the speed-and-bandwidth limitations of traditional cloud computing. By enabling on-site data processing, edge computing effectively low-latency and responsive applications, e.g., predictive maintenance, process optimization, and autonomous robotics. This paper discusses edge computing architecture and deployment models, its hardware and software components, and networking infrastructure. The objectives to review are to analyze how edge computing facilitates real-time decision-making in automated industrial processes. The discourse is then fully addressed around the different core technologies, advantages, concerns, real-life instances, and future trends toward increasing efficiencies, lowering latencies, and making smart manufacturing possible. Integration of AI and machine learning at the edge levels make real-time analytics, thus improving efficiency and agility. Key challenges under consideration include security, scalability, and economic impact, along with their applications in the real world. Future direction encompasses AI-based analytics, energy-efficient edge devices, and seamless interoperability poised to change its status from enabler to disrupter concerning industrial automation.

关键词： automation Reviews Decision making Process control Real-time systems Energy efficiency Security Optimization Interoperability Edge computing

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Towards Exact Interaction Force Control for Underactuated Quadrupedal Systems with Orthogonal Projection and Quadratic Programming

Towards Exact Interaction Force Control for Underactuated Qu...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Shengzhi Wang Xiangyu Chu K. W. Samuel Au Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

Projected Inverse Dynamics Control (PIDC) is commonly used in robots subject to contact, especially in quadrupedal systems. Many methods based on such dynamics have been developed for quadrupedal locomotion tasks, and only a few works studied simple interactions between the robot and environment, such as pressing an E-stop button. To facilitate the interaction requiring exact force control for safety, we propose a novel interaction force control scheme for under-actuated quadrupedal systems relying on projection techniques and Quadratic Programming (QP). This algorithm allows the robot to apply a desired interaction force to the environment without using force sensors while satisfying physical constraints and inducing minimal base motion. Unlike previous projection-based methods, the QP design uses two selection matrices in its hierarchical structure, facilitating the decoupling between force and motion control. The proposed algorithm is verified with a quadrupedal robot in a high-fidelity simulator. Compared to the QP designs without the strategy of using two selection matrices and the PIDC method for contact force control, our method provided more accurate contact force tracking performance with minimal base movement, paving the way to approach the exact interaction force control for underactuated quadrupedal systems.

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Distributed Photovoltaic Power Prediction Based on Spatiotemporal Attention Convolutional Networks under Weather-free Conditions

Distributed Photovoltaic Power Prediction Based on Spatiotem...

引用

2024 IEEE China international Youth conference on Electrical Engineering, CIYCEE 2024

作者： Peng, Xiaojin Luo, Bingyang Zhu, Guorong School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9798331530174

With the massive integration of distributed photovoltaic (PV) systems into the power grid, accurate forecasting of distributed PV power generation is of great significance for the stable operation of power systems. Existing methods often neglect the spatiotemporal correlations among distributed PV systems, making it difficult to effectivelyutilize spatiotemporal feature information to improve power forecasting accuracy. Considering the strong spatiotemporal correlations among distributed PV outputs and the difficulty in obtaining meteorological data, this paper proposes a distributed PV power forecasting method based on Spatial- Time-Attention, Graph Convolutional Network (GCN), and Temporal Convolutional Network (TCN). This method achieves accurate PV power prediction under weather-free conditions based solely on historical power data. First, the spatial-time attention mechanism is used to extract the spatiotemporal dependencies of the distributed PV cluster output. Next, GCN and TCN are utilized to construct a spatiotemporal graph convolutional network for prediction training, obtaining the forecasting results. Finally, a simulation is conducted based on real data from a distributed PV power plant in a certain region of China. The case study results show that the proposed model has higher accuracy compared to traditional deep learning models. © 2024 IEEE.

关键词： Photovoltaics

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Numerical and Experimental Assessment of Distributed Model Predictive Control of Multi-agent Circular Formation

Numerical and Experimental Assessment of Distributed Model P...

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international conference on Control, automation and Systems ( ICCAS)

作者： Seongheon Kim Guilherme Araujo Pimentel Yoonsoo Kim Alain Vande Wouwer School of Mechanical and Aerospace Engineering Gyeongsang National University Jinju Republic of Korea Systems Estimation Control and Optimization (SECO) University of Mons Mons Belgium

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This paper presents the development of a didactic robotic demonstrator to study the circular formation problem (CFP) of multi-agent systems based on Distributed Model Predictive Control (DMPC). CFP can arise in various fields, such as robotics, drones, and space applications. This study proposes a method for multiple agents to sequentially enter a circular orbit, one by one, and move along the orbit at a predefined speed while maintaining a desirable distance from each other. Due to the advantages of DMPC, the proposed method allows each agent to independently generate control inputs while considering various types of constraints related to collision avoidance with the other agents. The methodology is tested and validated with three differential drive robots, i.e., Turtlebots.

关键词： Space vehicles Predictive models Control systems Orbits Numerical models Collision avoidance Robots Predictive control Multi-agent systems Drones

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