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Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

ieee/CAA Journal of Automatica Sinica 2023年第8期10卷 1766-1768页

作者： Zhongbo Sun Shijun Tang Jiliang Zhang Junzhi Yu the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE College of Information Science and Engineering Northeastern UniversityShenyang 110819China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t... 详细信息

关键词： directional programming hardware

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6D Grasp Pose Detection in Cluttered Environment from a Single-view

6D Grasp Pose Detection in Cluttered Environment from a Sing...

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2023 ieee International Conference on robotics and Biomimetics, ROBIO 2023

作者： Li, Enbo Fu, Yili Feng, Haibo Intelligent Robot Research Center Zhejiang Laboratory Hangzhou311100 China Harbin Institute of Technology State Key Laboratory of Robotics and System Heilongjiang Province Harbin150001 China

ISBN: (纸本)9798350325706

Robot grasping has always been a hot topic in the research field, but there are still a lot of problems to be solved. In this paper, we propose a general grasping method for the unknown objects in cluttered environment from a single-view. Our method is divided into three steps: sampling points selection, grasping pose sampling and grasping pose evaluation. Firstly, we generate a pixel-wise probability image based on the trained sampling affordance network from RGB images, and map the points with high probability to the 3D point cloud combined with the depth map. Then, we obtaine the candidate grasps by sampling on the proposal points, and finally we evaluate the candidate grasps through the trained grasp evaluation network. The network can capture the geometric structure represented by the point cloud information. The proposed method directly uses the original sensor data and can increases the sampling success rate. © 2023 ieee.

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High-precision trajectory calibration for robot surface machining by meta-heuristic search algorithm from local error in machining area

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International Journal of Advanced Manufacturing Technology 2025年第5期138卷 2281-2295页

作者： Bi, Guangde Lu, Lei Zhang, Lei Fan, Cheng Sun, Lining School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou215123 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Industrial robots used in complex surface machining are gradually increasing because of their high flexibility and large workspace. However, due to their low geometric accuracy, their application in high-precision surface machining is hindered. In order to improve the machining accuracy, a high-precision robot trajectory calibration method for complex surface machining is proposed. In the machining process, the machining trajectory is usually only within a certain machining area. In the method, high-precision standard balls are set at the boundary of the machining area. Based on the precise position information of these standard balls, the trajectory of the robot in the machining area is calibrated. Compared with the global robot calibration method, the proposed method can calibrate the robot trajectory in the machining area through standard parts, which will improve the trajectory accuracy of the machining robot to the level of repeated positioning accuracy. In this method, a large amount of standard ball data is obtained by the in-place measuring device before the machining process. Then, based on these data, a meta-heuristic search algorithm is used to calibrate the kinematic deviation of the robot measurement and the machining system. The trajectory of the machining robot is adjusted by the kinematic deviation after calibration, and it is applied to the motion control of the machining process to improve the positioning accuracy of the machining trajectory. In the end, to verify the accuracy and practicability of the machining trajectory obtained by this method, measurement and machining experiments are carried out. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Industrial robots

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A Sample Repetitive Manipulation Mechanism (SRMM) for Lunar Regolith In-Situ Analysis: Design and Validation

A Sample Repetitive Manipulation Mechanism (SRMM) for Lunar ...

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2023 ieee International Conference on robotics and Biomimetics, ROBIO 2023

作者： Liu, Yi Tang, Junyue Liu, Yafang Ma, Gongbo Sun, Feng Li, Ye Jiang, Shengyuan Shenyang University of Technology Shenyang China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China Beijing Institute of Spacecraft System Engineering Beijing China Beijing China

ISBN: (纸本)9798350325706

To exactly detect the water ice of the South Pole of the moon, a lunar regolith in-situ analysis payload deploying a mass spectrometer is proposed for China future lunar exploration missions. In order to receive the lunar regolith sample from a robotic arm with a soil sampler and transfer it into a furnace for further analysis, a sample manipulation mechanism is required during the above work flow. To solve the problems of adapting the sampler's docking accuracy, receiving and transferring two different types of lunar soil sample under times of in-situ analysis, etc., a sample repetitive manipulation mechanism (SRMM) is proposed in this paper. By using a floating adjustable docking components and a flexible hopper, two types of encapsulated regolith sample and bulk material sample can be received with minimal sample loss, respectively. In order to receive and transfer two types of samples multiple times, two sample receiving methods have been designed that can be repeatedly transferred. A worm and worm wheel combined with a ball screw is designed in SRMM. To verify the above mechanism design, validation experiments were conducted. It indicates that this novel SRMM can be deployed in the future mission after further environmental tests. © 2023 ieee.

关键词： Lunar exploration Repeated transfer Sample type sampler's docking sealing force

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RAM-NAS: Resource-aware Multiobjective Neural Architecture Search Method for Robot Vision Tasks

RAM-NAS: Resource-aware Multiobjective Neural Architecture S...

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ieee/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Shouren Mao Minghao Qin Wei Dong Huajian Liu Yongzhuo Gao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Neural architecture search (NAS) has shown great promise in automatically designing lightweight models. However, conventional approaches are insufficient in training the supernet and pay little attention to actual robot hardware resources. To meet such challenges, we propose RAM-NAS, a resource-aware multi-objective NAS method that focuses on improving the supernet pretrain and resource-awareness on robot hardware devices. We introduce the concept of subnets mutual distillation, which refers to mutually distilling all subnets sampled by the sandwich rule. Additionally, we utilize the Decoupled Knowledge Distillation (DKD) loss to enhance logits distillation performance. To expedite the search process with consideration for hardware resources, we used data from three types of robotic edge hardware to train Latency Surrogate predictors. These predictors facilitated the estimation of hardware inference latency during the search phase, enabling a unified multi-objective evolutionary search to balance model accuracy and latency trade-offs. Our discovered model family, RAM-NAS models, can achieve top-1 accuracy ranging from 76.7% to 81.4% on ImageNet. In addition, the resource-aware multi-objective NAS we employ significantly reduces the model’s inference latency on edge hardware for robots. We conducted experiments on downstream tasks to verify the scalability of our methods. The inference time for detection and segmentation is reduced on all three hardware types compared to MobileNetv3-based methods. Our work fills the gap in NAS for robot hardware resource-aware.

关键词： Training Accuracy Image edge detection Scalability Robot vision systems Predictive models Hardware Neural architecture search Robots Testing

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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

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ieee/CAA Journal of Automatica Sinica 2022年第10期9卷 1778-1791页

作者： Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni IEEE the School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing Ministry of EducationSun Yat-sen UniversityGuangzhou 510006China the School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China the State Key Laboratory of Robotics and Systems Harbin Institute of Technology(HIT)Harbin 150080China

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

关键词： Dual zeroing neural networks(ZNN) finite-time convergence model-free robot control robustness analysis

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PMM-Net: Single-stage Multi-agent Trajectory Prediction with Patching-based Embedding and Explicit Modal Modulation

arXiv

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arXiv 2024年

作者： Liu, Huajian Dong, Wei Fan, Kunpeng Wang, Chao Gao, Yongzhuo State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Analyzing and forecasting trajectories of agents like pedestrians plays a pivotal role for embodied intelligent applications. The inherent indeterminacy of human behavior and complex social interaction among a rich variety of agents make this task more challenging than common time-series forecasting. In this letter, we aim to explore a distinct formulation for multi-agent trajectory prediction framework. Specifically, we proposed a patching-based temporal feature extraction module and a graph-based social feature extraction module, enabling effective feature extraction and cross-scenario generalization. Moreover, we reassess the role of social interaction and present a novel method based on explicit modality modulation to integrate temporal and social features, thereby constructing an efficient single-stage inference pipeline. Results on public benchmark datasets demonstrate the superior performance of our model compared with the state-of-the-art methods. The code is available at: ***/TIB-K330/pmm-net. Copyright © 2024, The Authors. All rights reserved.

关键词： Economic and social effects

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JHT-EXO: A Soft Ankle Exosuit for Assisting Walking in Patients with Post-Stroke Foot Inversion

JHT-EXO: A Soft Ankle Exosuit for Assisting Walking in Patie...

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ieee International Conference on robotics and Biomimetics

作者： Haotian Ju Zihang Guan Songhao Guo Zedong Liu Qinghua Zhang Tianjiao Zheng Jie Zhao Yanhe Zhu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Stroke often leads to foot inversion, seriously affecting the patients' walking ability. In this paper, a lightweight, soft exosuit, JHT-EXO, is proposed for correcting foot inversion to help patients' gait rehabilitation. JHT-EXO mainly consists of two cable driving modules, two foot feedback modules, and a control module, with a total weight of no more than 2.5 kg. The cable driving module can pre-tighten the cable with a designed constant torque spring to prevent the cable from falling off. When the motor is not energized, it can still assist the person in stabilizing the walking gait and reducing power consumption. Customized foot pressure sensors recognize human gait, and IMUs on the feet measure the ankle angle used by the controller to change the output force of the exosuit. The constant torque spring was calibrated and tested, and the experimental results showed that the average output force of the constant torque spring was 20.0 N, with a maximum error of 5.6% compared to the theoretically calculated results. The ground walking test of the exosuit was performed by three subjects in three conditions: wearing the exosuit powered up, wearing the exosuit unpowered, and not wearing the exosuit. The test results showed that JHT-EXO could effectively reduce the ankle inversion angle by $22.11^\circ$ compared to not wearing the exosuit. JHT-EXO is feasible in preventing foot drop and stabilizing flip, and its high mobility and portability show potential for gait rehabilitation of foot inversion patients.

关键词： Legged locomotion Ankle Pressure sensors Torque Force Stroke (medical condition) Pressure measurement Springs Robots Foot

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A Novel FBG Shape Sensor Based on Mechanical Model for Continuum Manipulator

A Novel FBG Shape Sensor Based on Mechanical Model for Conti...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Yuxin Zhang Wei Dong Zhiyuan Yan Yongzhuo Gao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

Fiber Bragg Gratings (FBG) are used widely for that it is small and sensitive. It is suitable to insert a sensor based on FBGs to some narrow cavities. At the same time, a slender continuum structure requires tiny sensors inside it. A multi-node differential curvature measurement sensor of FBG fiber is designed in this paper to realize temperature compensation. Considering the friction among FBG, driving wires, and niti tube and external forces applied on the end, a mechanical model about the FBG sensor and the continuum manipulator is proposed. At last, a linear interpolation method is used in the curvature estimation. Under the condition that there is no end resistance and only the bending moment and friction along the outer surface of the continuum generated by the steel wire driven by the motor the absolute measurement error of the position of the end of the continuum is 1.9mm.

关键词： Temperature measurement Temperature sensors Optical fiber sensors Shape Shape measurement Wires Robot sensing systems

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Acoustic black hole effect enhanced micromanipulator

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Microsystems & Nanoengineering 2024年第5期10卷 345-352页

作者： Qiu Yin Haoyong Song Zhaolong Wang Zhichao Ma Wenming Zhang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghaiChina institute of Medical Robotics School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina College of Mechanical and Vehicle Engineering Hunan UniversityChangshaChina School of Energy Science and Engineering Harbin Institute of TechnologyHarbinP.R.China

Microparticle manipulation is a critical concern across various felds including microfabrication,flexible electronics and tissue ***-activated sharp structures have been designed as simple and flexible tools to manipulate microparticles with their good compatibility,fast response,and broad ***,there still lacks rational acoustic-structure design for effective energy concentration at the acoustic-activated sharp structures for microparticle ***,we present the acoustic black hole(ABH)effect as enhancement for the acoustic *** provides great reliability,simplicity and ease of use,supporting custom design of high-throughput patterning ***,compared to commonly used configurations,such as cylindrical or conical microneedles,those microneedles with ABH profle exhibit superior acoustic energy focusing at the tip and induce stronger acoustofluidic *** average acoustic flow velocity induced by the ABH microneedle is 154 times greater than that of the conical one and 45 times greater than that of the cylindrical ***,the average acoustic radiation force(ARF)produced by the ABH microneedle against acrylic microparticles is about 319 times greater than that of the cylindrical one and 16 times greater than that of the conical *** results indicate that ABH design significantly enhances microparticle *** demonstrate this concept with ABH effect enhanced microparticle manipulation and study the parameters influencing its performance including operating frequency,operating voltage and particle ***,considering the flexibility of this system,we employ it for various patterning and high-throughput microparticle *** work paves the way for controllable microparticle manipulation,holding great potential for applications in microfabrication and biomedicine.

关键词： cylindrical Acoustic simplicity

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