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arXiv 2025年

作者： Mu, Xuan Liu, Xiaorui Guo, Shuai Chi, Wenzheng Wang, Wei Ge, Shuzhi Sam School of Automation Qingdao University Qingdao266000 China School of Automation Qingdao University Qingdao University Qingdao266000 China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou215021 China School of Mechanical Engineering & Automation the Robotics Institute Beihang University Beijing100000 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore

Nowadays robot is supposed to demonstrate human-like perception, reasoning and behavior pattern in social or service application. However, most of the existing motion planning methods are incompatible with above requirement. A potential reason is that the existing navigation algorithms usually intend to treat people as another kind of obstacle, and hardly take the social principle or awareness into consideration. In this paper, we attempt to model the proxemics of group and blend it into the scenario perception and navigation of robot. For this purpose, a group clustering method considering both social relevance and spatial confidence is introduced. It can enable robot to identify individuals and divide them into groups. Next, we propose defining the individual proxemics within magnetic dipole model, and further established the group proxemics and scenario map through vector-field superposition. On the basis of the group clustering and proxemics modeling, we present the method to obtain the optimal observation positions (OOPs) of group. Once the OOPs grid and scenario map are established, a heuristic path is employed to generate path that guide robot cruising among the groups for interactive purpose. A series of experiments are conducted to validate the proposed methodology on the practical robot, the results have demonstrated that our methodology has achieved promising performance on group recognition accuracy and path-generation efficiency. This concludes that the group awareness evolved as an important module to make robot socially behave in the practical scenario. © 2025, CC BY-NC-ND.

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Point, Segment, and Inspect: Leveraging Promptable Segmentation Models for Semi-Autonomous Aerial Inspection

Point, Segment, and Inspect: Leveraging Promptable Segmentat...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Riccardo Franceschini Javier Rodriguez Marquez Matteo Fumagalli Julian Cayero Becerra Eurecat Centre Tecnològic de Catalunya Robotics and Automation Unit Cerdanyola del Vallès Barcelona Spain Department of Electrical Engineering Automation and Control Group Danish Technical University Lyngby Denmark

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Operating unmanned aerial vehicles (UAVs) for assets inspections poses distinct challenges encompassing the need to maintain a safe distance from the inspection area, ensure correct orientation towards the inspected surface, and achieve comprehensive coverage of the entire surface. Achieving these tasks is inherently complex and stressful. Therefore, a novel approach that seeks to enhance the piloting experience by harnessing the latest advancements in segmentation models, such as Segment Anything Model (SAM), is proposed. These models, thanks to their prompting capabilities, allow seamless communication between the operator and the UAV, opening up the possibility of defining intricate inspection regions through simple interactions. Within this approach, decision-making authority remains with the operator, while the UAV takes on the demanding task of segmenting the designated area and devising an appropriate traversal plan. Throughout this process, the operator’s situational awareness is heightened through visual cues overlaid on the camera stream and a 3D panel presenting information of the drone position and spatially sensed data. This teleoperation framework allows the operator to maintain continuous control of the ongoing operation through a simplified interface. The paper delineates both the system and the methodology employed, showcasing the effectiveness of integrating segmentation models into the decision-making workflow. The validity of the proposed framework is established through testing within a photorealistic UAV simulator along with real experiments in a controlled laboratory environment.

关键词： Visualization Three-dimensional displays Decision making Laboratories Inspection Traveling salesman problems Autonomous aerial vehicles Robot sensing systems Spatial databases Surface treatment

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A Hollow FBG-Based 3-Axis Force Sensor for Surgical Robots

A Hollow FBG-Based 3-Axis Force Sensor for Surgical Robots

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Li, Jie Deng, Weiquan Wang, Chongyang Cheng, Haoning Cui, Junlin Liang, Ming Liu, Hao Shenyang Jianzhu University School of Mechanical Engineering Shenyang110168 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang1100169 China Key Laboratory of Minimally Invasive Surgical Robot Shenyang110016 China The General Hospital of Northern Theater Command of the Chinese People's Liberation Army Department of Cardiology China

ISBN: (纸本)9798350372601

The ability to perceive forces is crucial for surgical robots to perform operations safely and achieve effective treatment. This paper presents the design of a hollow force sensor based on fiber Bragg gratings (FBGs) to detect 3-Axis forces between the instrument and tissue. The sensor, consisting of an elastic body and four optical fibers with FBGs, is designed for convenient integration into instruments. Unlike most previous force sensors proposed by researchers, which fail to balance sensitivity across axes and have a hollow structure, the sensor designed in this paper positions the optical fibers away from the center to reserve sufficient space for the instrument channel. Additionally, the proposed elastic body comprises both an outer tube of flexible deformable beams and inner support pillars that enhance radial stiffness. This design ensures sensitivity along the axis while increasing stiffness against bending deformation radially. Furthermore, the force sensor is manufactured using 3D printing, making assembly simple and enabling easy interchangeability of instrument tips for various surgical instruments. Finite element simulations and experiments were conducted to verify the sensor's excellent linearity. The measurement range for each axis extends from 0 to 4 N. The axial resolution is 6 mN, while the radial resolution is 3.1 mN. At last, temperature compensation was implemented for the sensor environment to mitigate temperature-induced interference, ensuring precise measurements of three-Axis forces. The sensor is expected to be integrated into surgical robots to ensure surgical safety and enhance surgical quality. © 2024 IEEE.

关键词： Fiber Bragg gratings

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A miniaturized mechanical antenna based on FEP/ THV unipolar electrets for extremely low frequency transmission

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Microsystems & Nanoengineering 2022年第3期8卷 223-233页

作者： Yong Cui Ming Wu Zhaoyang Li Xiao Song Chen Wang Haiven Yuan Zhi-Xin Yang Junwen Zhong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Department of Electromechanical Engineering and Centre for Artificial Intelligence and Robotics University of MacaoMacaoSAR 999078China School of Cyber Science and Technology Beihang universityBeijing 100191China State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering University of MacaoMacaoSAR 999078China

An electret-based mechanical antenna(EBMA),which can transmit extremely low frequency(ELF)electromagnetic signals,has the advantages of miniaturization and high transmitting efficiency,with great potential applications in air,underwater,and underground *** improve the charge density of the electret,which is a key factor in determining the radiation performance of an EBMA,this work proposes a fluorinated ethylene propylene/terpolymer of tetrafluoroethylene,hexafluoropropylene and vinylidene fluoride(FEP/THV)unipolar electret exhibiting negative polarity,reaching a total charge density up to-0.46 mC/m^(2) for each layer of *** transmission distances can be achieved in sea water,soil,and air using a 3-layer-FEP/THV-based EBMA with a compact volume of 5×10^(-4) m^(3).As an application demonstration,binary ASili-coded ELF information of"BUAA"is successfully transmitted with a power consumption<5W.

关键词： antenna propylene FEP

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Detecting Postural Instability in Parkinson's Disease from IMU-based Objective Measures

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IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 2025年 PP卷 PP页

作者： Kendal Smith Diego Torricelli Miguel Gonzalez-Sanchez Javier Ricardo Perez-Sanchez Elisa Luque-Buzo Francisco Grandas Juan Miguel Marin J A Gomez-Garcia Department of Statistics Universidad Carlos III de Madrid Getafe Spain Center for Automation and Robotics Spanish National Research Council Arganda del Rey Spain Department of Neurology Hospital General Universitario Gregorio Marañón Madrid Spain

Parkinson's Disease (PD) is a progressive neurological disorder that affects both motor and non-motor functions. A critical aspect of PD is postural instability, which is associated with a higher risk of falls and a significant decline in mobility. The onset of postural instability is frequently identified through subjective clinical assessments such as the pull test, which aligns with the transition from Stage II to Stage III on the Hoehn and Yahr (H&Y) scale, a measure of general motor impairment. This study aims to pinpoint this transition by providing an objective quantification of the pull test, to prevent falls and manage severe motor symptoms via early detection. Sixty objective metrics were characterised from acceleration data using inertial measurement units (IMU) during pull tests conducted with 30 PD patients to differentiate between H&Y Stages II and III. Significant differences in feature distributions were identified, with two features achieving a ROC AUC of 0.95: chest to lumbar maximum acceleration ratio, and power ratio of 8-12 Hz versus total acceleration power. This paper demonstrates the ability of certain IMU-derived features to distinguish between H&Y Stages II and III, presenting more straightforward and objective measurements compared to conventional pull test metrics. Furthermore, the study explores the inconsistencies in the administration of the pull test by different examiners and shows that even with these inconsistencies, objective measures can still effectively differentiate between stages. To the best of our knowledge, this work represents the first extensive attempt to objectively quantify the pull test for this type of classification.

关键词： Motors Stability analysis Measurement Hospitals Life estimation Databases Wheelchairs Reliability Neurological diseases Measurement units

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Robot device for ankle joint rehabilitation: A review 55

Robot device for ankle joint rehabilitation: A review

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55th International Conference on Vibroengineering

作者： Zhetenbayev, Nursultan Zhauyt, Algazy Balbayev, Gani Shingissov, Beibit Department of Robotics and Engineering Tools of Automation Satbayev University Almaty050013 Kazakhstan Department of Electronics and Robotics Almaty University of Power Engineering and Telecommunications Almaty050013 Kazakhstan Academy of Logistics and Transport Almaty050012 Kazakhstan Space Engineering and Technology Almaty University of Power Engineering and Telecommunications Almaty050013 Kazakhstan

The purpose of this review document is to summarize the latest developments and research in the field of robotics related to the field of ankle joint rehabilitation, review new results, and determine the actual state of the art. The literature search was carried out using scientific and medical databases and other websites related to robots used in the field of ankle rehabilitation, analyzing research from the 1950s to the present. © 2022 JVE International. All rights reserved.

关键词： Machine design

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Development of a Measurment Method to Assess the Ice Adhesive Properties

Development of a Measurment Method to Assess the Ice Adhesiv...

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International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Margarita A. Baranova Alexey S. Osipkov Roman A. Poshekhonov Special Engineering Department Bauman Moscow State Technical University Moscow Russian Federation Robotics and Complex Automation Department Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Ice formation on the power and industrial equipment, such as power lines, wind turbines, solar panels, etc., could cause malfunctions or significant reduction in their performance. Solutions including the Ice-phobic Coating (IC) and, in particular, the anti-icing surfaces, are an efficient method in protecting the surfaces from icing. However, the ice adhesion strength values obtained by different research groups are difficult to be compared directly, as any unified standard for measuring the ice adhesion strength is missing, which causes significant variations in the results and makes it difficult to further implement the IC technique in practical applications. The paper analyses the sources of errors in the existing ice adhesion measurement techniques and develops a methodology that minimizes effect of the main influencing factors. An appropriate test bench with an efficient surface cooling system based on the Peltier element and the micro-breaking machine was designed and developed in implementing the technique, its purpose was to determine adhesion characteristics of the statically frozen ice using the horizontal shear method. In the future, the proposed methodology could become a basis for the standardized ice adhesion testing.

关键词： Temperature measurement Temperature distribution Adhesives Cooling Ice Wind turbines Coatings Velocity measurement Surface treatment Testing

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TacRot: A Parallel-Jaw Gripper with Rotatable Tactile Sensors for In-Hand Manipulation

TacRot: A Parallel-Jaw Gripper with Rotatable Tactile Sensor...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Zhang, Wuyi Xia, Chongkun Zhu, Xiaojun Liu, Houde Liang, Bin Tsinghua Shenzhen International Graduate School Center for Artificial Intelligence and Robotics Shenzhen518055 China Beijing University of Posts and Telecommunications School of Automation Beijing100876 China Tsinghua University Navigation and Control Research Center Department of Automation Beijing100084 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Finger dexterity and tactile perception are key capabilities for humans to manipulate objects within hand, as well as robots. Inspired by the thumb-forefinger dexterous manipulative movement, we devised a novel robotic finger with an active rotational tactile sensor (i.e. TacRot), and mounted the finger on a parallel-jaw gripper. By processing the high-resolution images of the vision-based tactile sensor, we achieved depth reconstruction of the surface and localization of the contact area. To improve gripping flexibility and stability, we applied a self-adaptive grasping strategy with real-time contact detection feedback, which performed 94% success rate in experiment. Based on the rotational actuator at the fingertip, we proposed two in-hand manipulation primitives: (1) pivot: fingertips co-rotating for object reorientation;(2) twist: fingertips contra-rotating for object spin. The primitives are theoretically analyzed and experimentally verified in two practical tasks: pivoting a paper cup under vertical constraints and twisting a screw with spin angle estimation. Our design and experiments demonstrate a feasible way to enhance the active tactile manipulation ability for common parallel-jaw grippers. © 2022 IEEE.

关键词： Grippers

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A Cost-Effective Smart Labor Assistance Trolley for Industrial Applications

A Cost-Effective Smart Labor Assistance Trolley for Industri...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Muneeb Zafar Sarmad Shafique Faisal Riaz Samia Abid Umar Raza William Holderbaum Department of CS & IT National Center of Robotics and Automation (NCRA) Control Automotive and Robotics (CAR) Mirpur University of Science and Technology Mirpur Pakistan Department of Engineering Manchester Metropolitan University Manchester United Kingdom

In the last couple of decades, autonomous human assistance robots have been enormously attracting the industrial sector. For this purpose, numerous researchers have contributed towards designing efficient and robust human assistance mechanisms. However, their proposed approaches do not provide a cost-effective solution due to the deployment of exorbitant sensors and sophisticated infrastructure. Besides, it was quite challenging for existing human-following robots to track their assigned human companion in different illusional states and luminous conditions while detecting obstacles and taking respective maneuvers (i.e., abrupt turns, etc.). Moreover, self-driving solutions need to take fast and real-time actions to avoid collisions in the designated environment. For this purpose, literature has shown the efficiency of YOLOv3 with respect to providing real-time results in latency-sensitive applications. Hence, to overcome this dilemma, we propose to develop an economically efficient deep learning- based smart labor assistance trolley that uses the YOLO v3 as a core detective deep learning technique with advance and efficient perception and motion planning modules. The perception module succours the autonomous trolley to precisely detect and classify the objects. While the motion planning module uses the specific intended target detection technique to follow the targeted person in crowded environment. These techniques make the autonomous trolley able to take expeditious, meticulous, and conspicuous action in real-time. The labor assistant robot detects and tracks the respective person using YOLOv3. To validate the efficiency of the proposed solution, we have performed a series of experiments considering different test cases. Our proposed work achieved a mean average precision of 0.81%.

关键词： automation Target tracking Service robots Transportation Object detection Robot sensing systems Real-time systems

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Adaptive Classifier to Address Concept Drift in Imbalanced Data Streams

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

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Data, Decision and Systems (ICDDS), IEEE International Conference on

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

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.

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