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The influence of Sodium Nitrate electrolyte on Aluminium scrapped wheel in the ECM process

Interactions 2024年第1期245卷 1-9页

作者： Vijayakumar, S. Rao, T. V. Janardhana Karumuri, Srikanth Manickam, Selvaraj Andhra Pradesh Odalarevu 533210 India Department of ECE BVC College of Engineering Andhra Pradesh Rajahmundry533102 India Department of Mechanical Engineering Mizan Tepi University Tepi Campus 121 Ethiopia Department of Automation and Robotics IMPACT College of Engineering and Applied Sciences Bangalore India

Electrochemical Machining (ECM) stands out as a non-traditional method for intricately shaping materials. It operates on the principles of Faraday’s laws of electrolysis, where the weight of the substance generated during electrolysis correlates directly with the current flow, process duration, and equivalent weight of the deposited material. This research specifically investigates assessing the impact of Sodium Nitrate (NaNO3) electrolyte on machining Aluminium scrapped wheel. Three ECM input parameters voltage, electrolyte concentration, and duty cycle are varied across different levels. The study scrutinizes machining outputs, particularly Material Removal Rate (MRR) and overcut (OC), employing the Taguchi design methodology. Optimal process factors are presumed through SN ratio analysis and ANOVA is utilized to analyze the contribution of each parameter to the output characteristics. The results of the study suggest that MRR is improved, and an optimal configuration consists of 10 V voltage, 90% duty cycle, and 25 g/l electrolyte concentration. to minimize OC, 12 V voltage, 80% duty cycle, and 25 g/l electrolyte concentration are recommended. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Sodium nitrate

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Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

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A practical PID variable stiffness control and its enhancement for compliant force-tracking interactions with unknown environments

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Science China(Technological Sciences) 2023年第10期66卷 2882-2896页

作者： ZHANG Xin ZHOU Hao LIU JinGuo JU ZhaoJie LENG YuQuan YANG ChenGuang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China School of Computing University of PortsmouthPortsmouth PO13HEUK Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Compliant interaction control is a key technology for robots performing contact-rich manipulation *** design of the compliant controller needs to consider the robot hardware because complex control algorithms may not be compatible with the hardware performance,especially for some industrial robots with low bandwidth *** paper focuses on effective and easy-to-use compliant control algorithms for position/velocity-controlled *** by human arm stiffness adaptation behavior,a novel variable target stiffness(NVTS)admittance control strategy is proposed for adaptive force tracking,in which a proportional integral derivative(PID)variable stiffness law is designed to update the stiffness coefficient of the admittance function by the force and position ***,its stability and force-tracking capability are theoretically *** addition,an impact compensator(Impc)is integrated into the NVTS controller to enhance its disturbance-suppression capability when the robot is subjected to strong vibration disturbances in complicated surface polishing *** proposed controllers are validated through four groups of experimental tests using different robots and the corresponding results demonstrate that they have high-accuracy tracking capability and strong adaptability in unknown environments.

关键词： compliant interaction control force tracking PID variable stiffness impact compensator unknown environments

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Uncover rock-climbing fish's secret of balancing tight adhesion and fast sliding for bioinspired robots

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National Science Review 2023年第8期10卷 222-231页

作者： Wenjun Tan Chuang Zhang Ruiqian Wang Yuanyuan Fu Qin Chen Yongliang Yang Wenxue Wang Mingjun Zhang Ning Xi Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Histology and Embryology Basic Medical CollegeChina Medical University Chengdu Institute of Biology Chinese Academy of Sciences Department of Biomedical Engineering School of Medicine Tsinghua University Emerging Technologies Institute Department of Industrial and Manufacturing Systems EngineeringUniversity of Hong Kong

The underlying principle of the unique dynamic adaptive adhesion capability of a rock-climbing fish（Beaufortia kweichowensis） that can resist a pull-off force of 1000 times its weight while achieving simultaneous fast sliding(7.83 body lengths per second（BL/S）) remains a mystery in the literature. This adhesion-sliding ability has long been sought for underwater robots. However, strong surface adhesion and fast sliding appear to contradict each other due to the need for high surface contact stress. The skillfully balanced mechanism of the tight surface adhesion and fast sliding of the rock-climbing fish is disclosed in this work. The Stefan force（0.1 mN/mm2） generated by micro-setae on pectoral fins and ventral fins leads to a 70 N/m2adhesion force by conforming the overall body of the fish to a surface to form a sealing chamber. The pull-off force is neutralized simultaneously due to the negative pressure caused by the volumetric change of the chamber. The rock-climbing fish's micro-setae hydrodynamic interaction and sealing suction cup work cohesively to contribute to low friction and high pull-off-force resistance and can therefore slide rapidly while clinging to the surface. Inspired by this unique mechanism, an underwater robot is developed with incorporated structures that mimic the functionality of the rock-climbing fish via a micro-setae array attached to a soft self-adaptive chamber, a setup which demonstrates superiority over conventional structures in terms of balancing tight underwater adhesion and fast sliding.

关键词： bioinspired underwater adhesion crawling robots rock-climbing fish Stefan adhesion underwater robots

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Adaptive Classifier to Address Concept Drift in Imbalanced Data Streams 2

Adaptive Classifier to Address Concept Drift in Imbalanced D...

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2nd IEEE International Conference on Data, Decision and Systems, ICDDS 2023

作者： Mulimani, Deepa Patil, Prakashgoud R. Totad, Shashikumar G. KLE Technological University Department of MCA Karnataka Hubballi India KLE Technological University Department of Automation and Robotics Karnataka Hubballi India

ISBN: (纸本)9798350314168

Concept drift adaptation is essential for maintaining the accuracy of machine learning models when facing changing data distributions in streaming environments. Class imbalance, a common issue in real-world datasets, further compounds the challenge of concept drift detection and adaptation. This paper proposes a comprehensive approach that focuses on effectively identifying and handling both concept drift and class imbalance to ensure the reliability and performance of predictive models. The approach involves two stages. First, a concept drift detection mechanism is employed to monitor the changing data distribution among the historical context of class distributions and adapts its sensitivity to class-wise changes. This minimizes the risk of false alarms while capturing subtle shifts in minority class distributions. Second, for concept drift adaptation, it uses ensemble-based resampling technique that dynamically adjusts the balance of classes by oversampling the minority class instances in a controlled manner. The approach is evaluated on synthetic and real-world streaming datasets with varying degrees of class imbalance and concept drift. Experimental results determine the advantage of the proposed method in comparison to baseline techniques in terms of detection accuracy and adaptability to changing conditions, particularly for underrepresented classes. © 2023 IEEE.

关键词： class imbalance concept drift minority class oversampling streaming data

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Formation Control and Sub-Swarm Generation of Multirotor UAVs

Formation Control and Sub-Swarm Generation of Multirotor UAV...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Shahzad, Muhammad Muzamal Asad, Muhammad Haroon Haris, Muhammad Munawar, Hammad Yousaf, Muhammad Haroon University of Engineering and Technology Taxila Swarm Robotics Lab National Center of Robotics and Automation Taxila Pakistan University of Engineering and Technology Taxila Computer Engineering Department Taxila Pakistan

ISBN: (纸本)9781665464727

The research field of collective behaviors takes inspiration from natural self-organizing systems like honeybees, fish schools, social insects, bird flocks, and other social animals. These behaviors can be transformed into robots by replicating the same set of rules as found in the natural swarms. The deployment of aerial swarm robotics has become significant due to their multiple applications in surveillance, agriculture, and military. These applications lead to the development of aerial swarm robotic platforms to solve real-world problems. For example, a swarm of low-tech, cost-effective small UAVs can engage a high-tech target effectively. Similarly, a swarm of UAVs can perform surveillance and rescue missions in disastrous areas and build an emergency communication network through multiple UAV swarms. The critical part of swarm technology is multiple swarm intelligence algorithms that have been proposed and tested by various simulation platforms such as V-rep, Gazebo and MATLAB. Very few of them have been deployed on hardware to solve real scenarios that include formation control, navigation, pattern formation, and a few sub-swarm generation algorithms. Team connectivity is one of the essential aspects of a swarm network that emerges the collective intelligence of the group and ensures the readiness of the algorithm to deploy and solve real-world problems. Many researchers proposed the team connectivity algorithms in a single swarm network but still left the connectivity gap between the sub-swarms during a mission. This research work contributes toward designing a swarm intelligence algorithm to improve the connectivity techniques and team connectivity between the swarm agents and the sub-swarm groups. © 2023 IEEE.

关键词： Antennas

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Geometric design of a kirigami gripper with form-enclosing grasping mode

Geometric design of a kirigami gripper with form-enclosing g...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Hu, Bingyan Du, Liang Wang, Mingyuan Bao, Sheng Yuan, Jianjun Ma, Shugen Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai University Shanghai Robotics Institute Shanghai China Ritsumeikan University Department of Robotics Shiga Japan

ISBN: (纸本)9798350325706

Although various grasp strategies have been proposed in soft gripper area, form-enclosing grasping mode always plays a marginal role because of the challenges to calculate the deformations of soft materials. In this study, we propose a easy-to-make kirigami gripper and a geometric optimization method to obtain the fingers boundary shape that achieves a complete form-enclosing grasping after bending. We used a FEM model to represent the finger shape and calculated the finger boundary, and then used a iterative method to find the best finger shape that generates the form-enclosing grasping result. The optimization method is based on the minimum energy rule, and has the advantages of being computationally efficient and being universal for optimizing the boundary of gripper with form-enclosing grasping mode. The effectiveness of the proposed method was validated by ANSYS simulation and practical experimental results. Moreover, an objective functions and multiple geometric constraints were derived to quantitatively evaluate the gripper designs. © 2023 IEEE.

关键词：

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Robotic System Performing Dynamic Interaction in Human-Robot Cooperative Work for Assembly Operation

Robotic System Performing Dynamic Interaction in Human-Robot...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Nakamura, Satoshi Arias, Carolina Higuera Bhardwaj, Mohak Boots, Byron Hitachi Ltd. Connective Automation Innovation Center R&d Group Robotics Research Department Japan University of Washington United States

ISBN: (纸本)9798350312072

In order to realize human-robot cooperative work, it is necessary to have dynamic interaction for unexpected human's motion that are difficult to define in advance. In this research, we propose a robotic system that supports operator work without interfering with human work by reacting and avoiding operator motion through real-time motion generation and activation re-planning. This system is included 3D recognition of the robot's surroundings and real-time motion generation technology. We implemented in the setup of assembly work assuming a high-mix, low-volume production site, and was demonstrated in a support task that robot distribute the parts for operator's assembly work. Experimental results show that the robot can conduct the cooperative work without interfering with operator work by performing appropriate avoidance actions against operator motion. © 2024 IEEE.

关键词： Robot programming

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Waste Sorting automation with Visual Sensor and RFID 3

Waste Sorting Automation with Visual Sensor and RFID

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3rd International Conference on Advanced Electrical Engineering, ICAEE 2024

作者： Seray, Seif Eddine Bey, Ishak Akli, Isma University of M'hammed Bouguerra Department of Control and Power Boumerdes Algeria Center for Development of Advanced Technologies Robotics and Industrial Automation Division Algiers Algeria

ISBN: (纸本)9798350349351

The quantity of domestic wastes is constantly increasing, resulting on overload of wastes. Recycling became imperative for ecologic and economical considerations in order to apply circular economy rules. In general, humans are recruited in waste sorting plants for performing the dangerous and tedious sorting tasks. The automation is, thus, necessary. This paper deals with the problem of waste sorting automation. The proposed solution consists of waste recognition and classification using YOLOv8, and human presence detection using RFID (Radio frequency Identification) tags. The proposed solution is validated in simulation. The virtual robot performs a task in order to simulate the behavior of a real robot with high fidelity, depending on the information coming from the RFID tags and a visual sensor. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

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Performance Analysis of Deepfake Text Detection Techniques on Social-media 2

Performance Analysis of Deepfake Text Detection Techniques o...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Gaur, Adamya Singh, Sanjay Kumar Saxena, Pranshu University School of Automation & Robotics Guru Gobind Singh Indraprastha University Delhi India Abes Engineering College Department of Information Technology Ghaziabad India

ISBN: (纸本)9798350382952

In the last few years, there has been remarkable progress in the domain of natural language generation & understanding. This has led to the development of enhanced text generation capability of machines that can generate spurious text or deepfake text. The technology may be exploited to change and shape public sentiment on social media. Therefore, mechanisms to detect deepfake text is a crucial task. The study emphasizes on detection of deepfake text on social media platform X (formerly Twitter). It presents the performance of machine learning classifiers Logistic regression (LR), XGB classifier, and AdaBoost classifier, utilizing feature engineering methods Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF). Deep learning methods such as Dense Neural Networks (DNN), Bi-directional Long Short-Term Memory (Bi-LSTM), and Convolutional Neural Networks (CNN)in addition to state-of-the-art models and variants such as Bi-Directional Encoder Representations from Transformers (BERT), DistilBERT & RoBERTa are also a part of study, leading to 89.17% accuracy in deepfake text detection. © 2024 IEEE.

关键词： Long short-term memory

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