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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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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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Construction of laser-induced graphene/silver nanowire composite structures for low-strain,high-sensitivity flexible wearable strain sensors

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Science China(Technological Sciences) 2024年第11期67卷 3524-3534页

作者： YANG PingAn ZHAO JingYuan LI Rui ZHOU ZhiHao GUI YinGang SUN RuiXue WU DeCheng WANG XiaoJie School of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Engineering and Technology Southwest UniversityChongqing 400715China Bio-inspired Robotics and Intelligent Material Laboratory Institute of Advanced Manufacturing TechnologyHefei Institutes of Physical ScienceChinese Academy of SciencesChangzhou 213164China

Sandwich-structured flexible sensors based on graphene have high sensitivity and *** graphene is combined with a flexible substrate in a sandwich structure,the weak bonding between them compromises the sensor's stability and sensitivity at low *** presents challenges in monitoring subtle physiological activities,such as hand bending and pulse *** this purpose,laser-induced graphene(LIG)is proposed to be used to prepare flexible sensors in order to improve the sensitivity and stability of the sensors at low ***(PDMS)with low modulus and polyimide(PI)with rich carbon content are selected as precursor materials for LIG,and graphene is formed through laser ***,silver nanowires(Ag NWs)solution is added to LIG to give the sensor low strain and high sensitivity *** the PI/PDMS ratio is 1:3,the Ag NWs/LIG flexible strain sensor exhibits excellent sensitivity(GF=778.468)over a small strain range(8.76%-11.25%).Meanwhile,the sensor still shows excellent stability after 2000 cycle *** Ag NWs/LIG flexible strain sensor shows good performance when placed on the back of the hand,around the eyes,*** is demonstrated that Ag NWs/LIG flexible strain sensors have good application potential in human physiological activity monitoring,health management and medical fields,and provide a low-strain,high-sensitivity sensor design strategy for flexible wearable devices.

关键词： flexible strain sensors high sensitivity strain range Ag NWs laser-induced graphene

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An Indoor Positioning Algorithm Against NLOS Error Based on UWB 41

An Indoor Positioning Algorithm Against NLOS Error Based on ...

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第41届中国控制会议

作者： Mingxiang Liao Yongbo Li Guangyao Wang Zhenyu Lei Zihao Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Ultra-wideband（UWB） positioning technology has absolute advantages due to its centimeter-level accurate positioning ***,the positioning accuracy is greatly reduced because of the inability to completely solve the error caused by non-line-of-sight（NLOS） and multi-path *** present,the Chan-Taylor（C-T） combination algorithm proposed by scholars can achieve a good positioning effect in the line-of-sight（LOS） environment,but in the NLOS environment,positioning deviation of this algorithm is large .Aiming at the problem of low localization accuracy in NLOS environment,this paper presents a Chan-Taylor-Kalman（CTK） joint positioning algorithm based on UWB and adapted to NLOS *** basic idea of CTK joint positioning algorithm is to introduce weight coefficients on the basis of C-T combination algorithm to reduce the situation of non-convergence of positioning results;then combined with the improved Kalman filter to eliminate outliers and eliminate the influence of the non-line-of-sight *** show that under the same NLOS environment,the probability of the positioning error of the C-T combination positioning algorithm greater than 20 cm is about 60%,while the probability of the positioning error of the CTK joint positioning algorithm greater than 10 cm is only about 10%.

关键词： UWB NLOS indoor positioning Chan-Taylor combination algorithm Kalman filter

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Kinematics analysis of lower limb rehabilitation robot based on D-H method 41

Kinematics analysis of lower limb rehabilitation robot based...

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第41届中国控制会议

作者： Kui Jie Wangyong He Renjie Gui School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

At present,rehabilitation robots usually work together with patients and train them to achieve therapeutic effects by assisting them to complete movement within a certain *** this paper,it analyzes the average length and proportion of Chinese human lower limbs,as well as the range of extreme motion and comfortable motion of each joint of human lower *** on the error transfer matrix of rigid body connecting rod,the three-DOF lower limb rehabilitation robot human lower limb static pose error model and human/machine integration model are *** D-H method was used to solve the kinematic function between the angle of each joint and the position of the end of human lower *** analysis of the kinematics of human lower limbs is to calculate its inverse kinematics *** the motion control of rehabilitation robots,the inverse kinematics is more important than the forward kinematics,which is the basis for rehabilitation robot to realize trajectory planning under the training mode of passive trajectory traction,as well as the basis for compliant ***,a simulation model is established with Matlab software,and the simulation results show the feasibility and safety of the rehabilitation training process.

关键词： Lower limb rehabilitation robot Range of motion Human kinematics

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Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1237-1250页

作者： Guangli Ren Jierui Liu Mengyao Wang Peiyu Guan Zhiqiang Cao 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 Peking UniversityBeijing 100871China

Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated *** transfer learning-based solution becomes popular due to its simple training with good accuracy,however,it is still challenging to enrich the feature diversity during the training *** fine-grained features are also insufficient for novel class *** deal with the problems,this paper proposes a novel few-shot object detection method based on dual-domain feature fusion and patch-level *** original base domain,an elementary domain with more category-agnostic features is superposed to construct a two-stream backbone,which benefits to enrich the feature *** better integrate various features,a dual-domain feature fusion is designed,where the feature pairs with the same size are complementarily fused to extract more discriminative ***,a patch-wise feature refinement termed as patch-level attention is presented to mine internal relations among the patches,which enhances the adaptability to novel *** addition,a weighted classification loss is given to assist the fine-tuning of the classifier by combining extra features from FPN of the base training *** this way,the few-shot detection quality to novel class objects is *** on PASCAL VOC and MS COCO datasets verify the effectiveness of the method.

关键词： few-shot object detection dual-domain feature fusion patch-level attention

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Strain sensor on a chip for quantifying the magnitudes of tensile stress on cells

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Microsystems & Nanoengineering 2024年第3期10卷 305-315页

作者： Yuyin Zhang Yue Wang Hongze Yin Jiahao Wang Na Liu Songyi Zhong Long Li Quan Zhang Tao Yue School of Mechatronics Engineering and Automation Shanghai UniversityShanghaiChina School of Future Technology Shanghai UniversityShanghaiChina Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhouChina Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghaiChina Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghaiChina

During cardiac development,mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number,area,and arrangement ***,the response of cells to different degrees of mechanical stimuli is ***-on-a-chip,as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment,is limited by the lack of ability to accurately quantify externally induced ***,previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external ***,we designed a cell stretching platform with an in-situ *** in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on *** platform was applied to human cardiomyocytes(AC16)under cyclic strain(5%,10%,15%,20 and 25%),and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify,and stabilized the cells at 15%amplitude,which was even more effective after 3 days of *** platform’s precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

关键词： stress deformation arrangement

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Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network 42

Temperature Rising Model of Tubular Permanent Magnet Linear ...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, YiFei Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network (TL-DNN) was proposed in this paper. Its specific implementation steps include (1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models (random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Finite element method

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A Weighting Factors Autotuning Strategy for Model Predictive Torque Control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

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42nd Chinese Control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Cost functions

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Comprehensive Performance Optimization of a Novel Anthropomorphic Dexterous Hand

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IEEE robotics and automation Letters 2025年第7期10卷 6816-6823页

作者： Ma, Yifan Shang, Weiwei Zhang, Fei Pang, Shunxiang Dai, Shuqing Yi, Zhengkun Li, Guotao Cong, Shuang University of Science and Technology of China Department of Automation Jinzhai Road 96 Hefei230027 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China

Grasp and in-hand manipulation of dexterous hands are essential for daily operational tasks. In this study, an optimized design method for a novel anthropomorphic dexterous hand is proposed, which improves the comprehensive performance of grasp and manipulability of the dexterous hand. The constraints of multi-fingered contact force and kinematics are established with full consideration of the applicability to the objects of different sizes and the shape characteristics of finger contact surface. The performance index of in-hand manipulation ability is proposed, and the optimization problem is constructed through the technique for order preference by similarity to ideal solution (TOPSIS) to achieve multi-objective optimization of precision grasp and in-hand manipulation. Finally, simulation and experiment verify the feasibility of our prototype and optimization method. The results show that the in-hand translation space and in-hand rotation range are increased by 20% and 8.5%, respectively. Our dexterous hand has excellent abilities of multi-fingered interaction and in-hand manipulation, which can perform 33 grasp gestures and two/three-fingered in-hand manipulation. This study provides a valuable reference for the design of dexterous hands with anthropomorphic functions. © 2016 IEEE.

关键词： Multiobjective optimization

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