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Soft Resource Slicing for Industrial Mixed Traffic in 5G Networks

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 463-465页

作者： Jingfang Ding Meng Zheng Haibin Yu the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Chinese Academy of Sciences the Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences the University of Chinese Academy of Sciences IEEE

Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.

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Contact Force Optimization to Enhance Fault-tolerant Motion Stability of a Hexapod Robot

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Journal of Bionic Engineering 2024年第5期21卷 2199-2214页

作者： Bo You Shangdong Shi Chen Chen Jiayu Li Nan Li Liang Ding The Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education and the Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

This paper presents a novel method for optimizing the contact force of a hexapod robot to enhance its dynamic motion stability when one of its legs *** proposed approach aims to improve the Force Angle Stability Margin(FASM)and adapt the foot trajectory through contact force optimization to achieve safe and stable motion on various *** foot force optimization approach is designed to optimize the FASM,a factor rarely considered in existing contact force optimization *** formulating the problem of enhancing the motion stability of the hexapod robot as a Quadratic Programming(QP)optimization problem,this approach can effectively address this *** of a hexapod robot using a fault-tolerant gait,along with real field experiments,were conducted to validate the effectiveness and feasibility of the contact force optimization *** results demonstrate that this approach can be used to design a motion controller for a hexapod robot with a significantly improved motion *** summary,the proposed contact force optimization method offers a promising solution for enhancing the motion stability of hexapod robots with single leg failures and has the potential to significantly advance the development of fault-tolerant hexapod robots for various applications.

关键词： Hexapod robot Fault-tolerant Stability margin Contact force optimization

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Position-aware pushing and grasping synergy with deep reinforcement learning in clutter

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 738-755页

作者： Min Zhao Guoyu Zuo Shuangyue Yu Daoxiong Gong Zihao Wang Ouattara Sie Intelligent Robotics Laboratory Faculty of Information TechnologyBeijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent Systems BeijingChina Laboratory of Biomechatronics and Intelligent Robotics(BIRO) Department of Mechanical and Aerospace EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA

The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in *** effectively perform grasping and pushing manipu-lations,robots need to perceive the position information of objects,including the co-ordinates and spatial relationship between objects(e.g.,proximity,adjacency).The authors propose an end-to-end position-aware deep Q-learning framework to achieve efficient collaborative pushing and grasping in ***,a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high-quality affordance maps of operating positions with features of pushing and grasping *** addition,the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial re-lationships between objects in cluttered *** further enhance the perception capacity of position information of the objects,the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function.A series of experiments are carried out in simulation and real-world which indicate that the method improves sample efficiency,task completion rate,grasping success rate and action efficiency compared to state-of-the-art end-to-end *** that the authors’system can be robustly applied to real-world use and extended to novel *** material is available at https://***/NhG\_k5v3NnM}{https://***/NhG\_k5v3NnM.

关键词： deep learning deep neural networks intelligent robots

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Automatic Control of Magnetic Helical Microrobots Docking with Target Objects in Liquid Environments

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Journal of Bionic Engineering 2025年第2期22卷 574-584页

作者： Fu Zhao Haoran Rong Lefeng Wang State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150080China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080China

Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.

关键词： Magnetic actuation Helical microrobots Visual servo Motion control Docking

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Efficient Nonnegative Tensor Decomposition Using Alternating Direction Proximal Method of Multipliers

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Chinese Journal of Electronics 2024年第5期33卷 1308-1316页

作者： Deqing WANG Guoqiang HU State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Marine Robotics Liaoning Province College of Artificial Intelligence Dalian Maritime University

Nonnegative CANDECOMP/PARAFAC（NCP） tensor decomposition is a powerful tool for multiway signal processing. The alternating direction method of multipliers（ADMM） optimization algorithm has become increasingly popular for solving tensor decomposition problems in the block coordinate descent framework. However,the ADMM-based NCP algorithm suffers from rank deficiency and slow convergence for some large-scale and highly sparse tensor data. The proximal algorithm is preferred to enhance optimization algorithms and improve convergence properties. In this study, we propose a novel NCP algorithm using the alternating direction proximal method of multipliers（ADPMM） that consists of the proximal algorithm. The proposed NCP algorithm can guarantee convergence and overcome the rank deficiency. Moreover, we implement the proposed NCP using an inexact scheme that alternatively optimizes the subproblems. Each subproblem is optimized by a finite number of inner iterations yielding fast computation speed. Our NCP algorithm is a hybrid of alternating optimization and ADPMM and is named *** experimental results on synthetic and real-world tensors demonstrate the effectiveness and efficiency of our proposed algorithm.

关键词： Tensors Neuroscience Signal processing algorithms Linearization techniques Signal processing Fluorescence Data processing

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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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Theoretical Model Construction and Static Performance Analysis of Multi-Leaf Journal Foil Bearings

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Journal of Tribology 2025年第7期147卷 074101页

作者： Hu, Yang Ding, Pengjing School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200072 China

Multi-leaf journal foil bearing (MLJFB) structures are complex, making performance prediction challenging, and the accurate prediction of gas film thickness and pressure distributions is crucial. In this study, comsol finite-element software was used to establish an initial foil assembly and structural deformation simulation model for an MLJFB with bump foils. Using matlab, a compressible gas lubrication model was established and solved using the finite volume method. Real-time data transfer between comsol and matlab enabled a fully coupled fluid-structure interaction simulation. This model meticulously accounts for the pre-tension force in the multi-leaf bearing assembly, contact friction between adjacent foils, and the interaction between the top foil and gas film pressure. The effects of journal movement distance, direction, and top foil overlapping ratio on the bearing capacity as well as the effects of different external load directions on the journal equilibrium position were analyzed based on this model. The results indicate that increasing the top foil overlapping ratio enhances the bearing capacity of the MLJFB. Furthermore, compared to the direction of the top foil overlap position, external loads applied in the direction of the top foil midpoint are more beneficial for bearing operational stability. Copyright © 2024 by ASME.

关键词： MATLAB

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Bio-syncretic robots composed of biological and electromechanical systems

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国家科学评论（英文版） 2023年第5期10卷 12-15页

作者： Chuang Zhang Jia Yang Wenxue Wang Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesChina Institute for Robotics and Intelligent Manufacturing Chinese Academy of SciencesChina State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesChina Institute for Robotics and Intelligent Manufacturing Chinese Academy of SciencesChina University of Chinese Academy of Sciences China

After eons of evolution,biological systems have developed excellent perfor-mance in terms of sensing,intelligence,and actuation—the three primary robotics elements that are closely re-lated to the overall performance of robot *** example,the buccal pits of some snakes,as the necessary sensors for accurate predation,have a high-temperature sensitivity of 0.003 K[1];the biological brain can exhibit an excellent capacity for efficient learning and multitasking operations[2];and froghopper insects can leap to a height of more than 100 times their body length[3].Most of these biological system per-formances are difficult to realize with tra-ditional electromechanical systems.

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Multi-modal Bionic Motion Analysis of A Cpg-controlled Pneumatic Soft Robot

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Journal of Bionic Engineering 2024年第5期21卷 2247-2257页

作者： Yu Zhang Peiyu Huang Dongjie Li Jiangyu Zhou Yu Li Bo You Yanhe Zhu Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin150001China

This paper designs a soft robot with a multi-chamber,multi-airbag mimicking soft biological structure,where the airbags of the same chamber are interconnected with each *** upper and lower chambers are separated by an intermediate layer(thin plate),which is extended and widened to achieve robot movement and *** applying pressure to the different chambers of the soft robot,it is possible to produce a variety of bionic movements of the inchworm and *** to the strong nonlinearity and infinite number of degrees of freedom properties of the material,it is impossible to obtain the analytical solution of the bending morphology and pressure of the soft robot ***,a method to establish a mathematical model of soft robot deformation based on the classical stacked plate theory is proposed,and a chain composite model of soft robot bending motion is established based on the large-deflection modeling *** paper proposes a method to generate a multi-mode soft robot motion control based on the Central Pattern Generator(CPG)using a single controller,which achieves the switching of sine wave-like patterns,half-wave-like patterns,and dragging patterns by adjust-ing frequency,amplitude and period of ***,a pneumatic control platform is built for the validation of the theoretical model and different experimental models of the motion of the *** comparation of the different motion modes of the soft robot under similar non-load and load conditions.

关键词： Soft robot Bionic multi-modal movement Laminated plate theory CPG control

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PCE: Multi-Agent Path Finding via Priority-Aware Communication & Experience Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年 1-13页

作者： Gao, Jianqi Li, Yanjie Ye, Zhaohui Wu, Xinyu Department of Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE

关键词： Aggregates

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