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Underwater RGB-D imaging system with millimetric precision

Science China(Information Sciences) 2024年第10期67卷 383-385页

作者： Yajun GAO Yang CONG Xu TANG Mingxue LI 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 College of Automation Science and Engineering South China University of Technology

In recent years, underwater fine three-dimensional reconstruction technology has emerged as a focal point in research, exhibiting extensive potential applications, particularly in underwater archaeology and resource e...

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A trajectory-level robot skill learning method based on fuzzy systems

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Science China(Information Sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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Teleoperation with automatic posture regulation and broad learning control for assembly tasks

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Science China(Information Sciences) 2024年第11期67卷 359-360页

作者： Liwen SITU Zhenyu LU Chenguang YANG School of Automation Science and Engineering South China University of Technology Bristol Robotics Laboratory University of the West of England

In recent years, robot teleoperation systems have been widely used in assembly tasks due to their ability to combine human control with robotic execution, addressing limitations in precision, perception, and intelligence faced by fully automated robots. However, robot teleoperation for assembly tasks still encounters several challenges. In complex and unstructured environments, telerobots must regulate the posture of their manipulators to avoid obstacles and singularities, ensuring the safety of human operators [1].

关键词： Remote control

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Autonomous Vehicle Lane Change Maneuver: A Comprehensive Analysis 2

Autonomous Vehicle Lane Change Maneuver: A Comprehensive Ana...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Paul, Sayandip Hemanth Kumar, C. Bongale, Arunkumar Symbiosis Institute of Technology Robotics and Automation Pune India

ISBN: (纸本)9798350306415

The two main parts of an autonomous vehicle lane change maneuver system are a lane change planner and a lane change controller. This paper describes a model-based design strategy for developing such a system. This means that the lane change planner is in charge of creating a lane change trajectory that is both safe and efficient. The lane-changing controller is tasked with the actual execution of the trajectory, involving the management of the vehicle's steering, acceleration, and braking. The lane change planner utilizes several strategies to craft trajectories that prioritize safety and efficiency. The planner starts with a time-to-collision analysis to determine which targets are safe or hazardous. If the present lane is considered safe, it then generates terminal states that are specific for the front automobile following modes. The lane changing maneuver system underwent evaluation within a simulation environment. The results of this assessment demonstrate the system's capability to adeptly and securely execute lane change maneuvers across diverse driving scenarios. © 2024 IEEE.

关键词： Lane change levels of autonomy model-based design time to collision analysis trajectory planning

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Cooperative output regulation of heterogeneous directed multi-agent systems:a fully distributed model-free reinforcement learning framework

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Science China(Information Sciences) 2025年第2期68卷 170-185页

作者： Xiongtao SHI Yanjie LI Chenglong DU Huiping LI Chaoyang CHEN Weihua GUI Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and AutomationHarbin Institute of Technology (Shenzhen) School of Automation Central South University School of Marine Science and Technology Northwestern Polytechnical University School of Information and Electrical Engineering Hunan University of Science and Technology

In this paper, the cooperative output regulation(COR) problem of a class of unknown heterogeneous multi-agent systems(MASs) with directed graphs is studied via a model-free reinforcement learning(RL) based fully distributed eventtriggered control(ETC) strategy. First, we consider the scenario that the exosystem is accessible globally to all agents, an internal model-based augmented algebraic Riccati equation(AARE) is constructed, and its solution is learned by the proposed model-free RL algorithm via online input-output data. Further, for the scenario that the exosystem is accessible only to its adjacent followers, the distributed observers are designed for each agent to get the state of the exosystem, and an internal modelbased fully distributed adaptive ETC protocol is then synthesized to construct the corresponding AARE, and the feedback gain matrix is learned in a model-free fashion. The model-free RL-based control protocol proposed in this paper can not only remove the prior knowledge of agents' dynamics, but also release the dependence on global information by the adaptive event-triggered mechanism(ETM) and the new graph-based Lyapunov function. Finally, simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.

关键词： model-free reinforcement learning unknown heterogeneous multi-agent systems fully distributed event-triggered control directed graph

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JADFER: Exploring Spatial-Contextual Interaction With Joint Attention Dropping for Facial Expression Recognition

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IEEE Transactions on Affective Computing 2025年第2期16卷 655-668页

作者： Gao, Yu Ren, Weihong Jiang, Weibo Dong, Qian Nie, Wei Wu, Wenhao Liu, Honghai Harbin Institute of Technology State Key Lab of Robotics and Systems School of Mechanical Engineering and Automation Shenzhen518055 China

Facial Expression Recognition (FER) aims to cate-gorize emotional expressions depicted on a human face, and isa challenging task under unconstrained conditions, such as faceocclusions and pose variations. Recent methods usually adopt selfattention or cross attention to explore global or local relationshipsamong different level features. However, these methods are inclinedto focus on the redundant facial regions, causing model *** address this problem, we propose a new FER model namedJADFER, which drops the joint attention in the weight matrix toadaptively enhance facial expression representations. Specifically,our JADFER model consists of three components: Spatial Branch(SB), Contextual Branch (CB), and Spatial-Contextual Interaction(SCI). First, SB runs N paths in parallel, where a Variety loss is de-signed to guide the paths of SB to focus on different discriminativeregions. Meanwhile, CB abstracts the contextual facial represen-tations using self attention with Joint Attention Dropping (JAD).Then, the SCI adopts the spatial features from SB to query thecontextual representations from CB through cross attention withJAD, which regulates the attention weights by dropping the similaractivations to further enhance the facial embeddings. Experimen-tal results demonstrate that the proposed model outperforms thestate-of-the-art methods on several FER benchmarks. © 2010-2012 IEEE.

关键词： Face recognition

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A Comprehensive Study on Weather Predicting automation Bot Using automation Software and Machine Learning

A Comprehensive Study on Weather Predicting Automation Bot U...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Joshi, Vedant Jadhav, Priya Symbiosis Institute of Technology Robotics and Automation Department Pune India

ISBN: (纸本)9798350361537

Weather forecasting is crucial in our daily lives, influencing everything from when to walk outside to what to dress. In this era of automation and data-driven decision-making, a new and reliable way of weather prediction is now possible thanks to the collaboration of automation software and machine learning. This study closely investigates the development and implementation of an automation bot for weather forecasting that employs machine learning and automation software techniques. This study investigates the complexity of this automation system, the underlying algorithms, its ease of use, and the accuracy of the forecasts it generates. The study shows how this unique concept not only increases weather forecast accuracy but also mentions the procedure, making it more accessible to users in daily life. This study shows the significant advancement in weather forecasting by combining the use of automation software with data-driven insights from machine learning. This will help in a more accurate and precise real-time understanding of climate change. © 2024 IEEE.

关键词： Machine learning algorithms Robotic Process automation Weather prediction

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Label-free and rapid mechanics of single cells under high-density co-culture conditions by deep learning image recognition-assisted atomic force microscopy

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生物化学与生物物理学报（英文版） 2025年第2期57卷 317-320页

作者： Xuliang Yang Mi Li State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China School of Artificial Intelligence Shenyang University of TechnologyShenyang 110870China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China

Mechanical cues play an important role in regulating cellular *** are able to sense and respond to the mechanical cues present in the extracellular physical microenvironment via mechan-otransduction[1],which can ultimately shape the functions and behaviors of the cells themselves as well as their microenviron-ments during numerous developmental,physiological and patho-logical processes[2].The development of human diseases such as cancer is generally accompanied by unique changes in the mechanical properties of cells and their physical microenviron-ments,and discoveries in the field of physical oncology are beginning to be translated into new therapeutic strategies for cancer[3].

关键词： label-free conditions mechanics learning rapid image force single cells deep

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Development of a cable-driven redundant space manipulator with large bending angle by combining quaternion joints and segmented coupled linkages mechanism

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Chinese Journal of Aeronautics 2023年第11期36卷 483-499页

作者： Taiwei YANG Jian HUANG Wenfu XU Ke SHAO Bin LIANG School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Department of Automation Tsinghua UniversityBeijing 100854China

A cable-driven redundant manipulator has significant potential in confined space applications, such as environmental exploration, equipment monitoring, or maintenance. A traditional design requires 3N driving motors/cables to supply 2N degrees of freedom(DOF) movement *** number of motors is 1.5 times that of the joints’ DOF, increasing the hardware cost and the complexity of the kinematics, dynamics, and control. This study develops a novel redundant space manipulator with decoupled cable-driven joints and segmented linkages. It is a 1680 mm continuum manipulator with eight DOF, consisting of four segmented linkages driven by eight motors/pairs of cables. Each segment has two equivalent DOF, which are realized by four quaternion joints synchronously driven by two linkage cables. The linkage cables of adjacent joints are symmetrically decoupled and offset at 180°. This design allows equal-angle movement of all the joints of each segment. Moreover, each decoupling driving mechanism is designed based on a pulley block composed of two fixed and movable pulleys. The two movable pulleys realize the opposite but equidistant motions of the two driving cables, i.e., pulling and loosening, assuring symmetrical movements of the two driving cables of each segment. Consequently, the equivalent 2N-DOF joints are driven only by 2N motors, significantly reducing the hardware cost and simplifying the mapping relationship between the motor angle/cable length and the joint angle. Furthermore, the bending range of each segment could reach 360°, which is three times that of a traditional design. Finally, a prototype has been developed and experimented with to verify the performance of the proposed mechanism and the corresponding algorithms.

关键词： Cable-driven Mechanism design Redundant manipulators Segmented linkages Kinematics

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Milling Tool Wear Estimation Using Machine Learning with Feature Extraction Approach

Milling Tool Wear Estimation Using Machine Learning with Fea...

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2024 MIT Art, Design and technology School of Computing International Conference, MITADTSoCiCon 2024

作者： Misal, Aarya Karandikar, Hrishikesh Sayyad, Sameer Bongale, Arunkumar Kumar, Satish Warke, Vivek Symbiosis Institute of Technology Dept. of Robotics and Automation Pune India

ISBN: (纸本)9798350362879

A cutting tool in any milling operation eventually becomes less efficient due to wear, which could result in reduction of quality and dimensional accuracy of the product during manufacturing. Precise and continuous monitoring is required to avoid these issues in machining. Manual inspection and arbitrary assessment have traditionally been used to identify faults and categorise machine tool wear. However, this method is time consuming and is prone to errors. The purpose of this study is to offer more effective, reliable, and accurate methods to predict tool wear using various data-driven machine learning models, which can then be used to determine Remaining Useful Life (RUL) of the milling tool. This paper implements the IEEE NUAA Ideahouse tool wear dataset containing various sensor readings and makes use of the TSFEL (Time Series Feature Extraction Library) for automatic feature extraction in the temporal, spectral and statistical domain, followed by the implementation of PCC (Pearson's Correlation Coefficient) for the selection of features that have a significant impact on tool wear. ML models such as K-Nearest Neighbors, Decision Tree, and Random Forest provides fairly good results with scaled data followed by feature extraction. All the models are evaluated based on MSE, MAPE and R2 score, by passing unscaled and scaled selected features in temporal, spectral and statistical domains to find out the model best suited for accurate tool wear prediction in order to assist in predictive maintenance. © 2024 IEEE.

关键词： Feature extraction

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