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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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Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第9期9卷 1-8页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Wu, Xinyu Department of Control Science and Engineering Harbin Institute of Technology Shenzhen and Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive Control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE

关键词： Reinforcement learning

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Obstacle avoidance in human-robot cooperative transportation with force constraint

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Science China(Information Sciences) 2023年第1期66卷 334-335页

作者： Ying ZHANG Chenguang YANG Sheng XU Yongsheng OU College of Automation Science and Engineering South China University of Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences

Dear editor,Robots are often conceived as human-like machines that can interact with humans naturally and safely. Human-robot interaction means that robots can communicate with people,understand their needs, and act accordingly [1]. This interaction is critical when two people are needed to finish a task cooperatively.

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General Kinetostatic Modeling and Deformation Analysis of a Two-Module Rod-Driven Continuum Robot with Friction Considered

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Chinese Journal of Mechanical Engineering 2023年第3期36卷 110-122页

作者： Peiyi Wang Xinhua Yang Xiangyang Wang Sheng Guo School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518005China

Continuum robots actuated by flexible rods have large potential applications,such as detection and operation tasks in confined environments,since the push and pull actuation of flexible rods withstand tension and compressive force,and increase the structure's *** this paper,a generalized kinetostatics model for multi-module and multi-segment continuum robots considering the effect of friction based on the Cosserat rod theory is ***,the model is applied to a two-module rod-driven continuum robot with winding ropes to analyze its deformation and load *** different in-plane configurations under the external load term as S1,S2,C1,and C2 are *** a bending plane as an example,the tip deformation along thex-axis of these shapes is simulated and compared,which shows that the load capacity of C1 and C2 is generally larger than that of S1 and ***,the deformation experiments and simulations show that the maximum error ratio without external loads relative to the total length is no more than 3%,and it is no more than 4.7%under the external *** established kinetostatics model is proven sufficient to accurately analyze the rod-driven continuum robot with the consideration of internal friction.

关键词： Rod-driven continuum robot Kinetostatic model Cosserat rod theory Deformation and stiffness analysis

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Pressure Pain Recognition for Lower Limb Exoskeleton Robot with Physiological Signals 1

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2nd International Conference on Cognitive Computation and systems, ICCCS 2023

作者： Ma, Yue Wu, Xinyu Wang, Xiangyang Li, Jinke Qin, Pengjie Yin, Meng Cao, Wujing Yi, Zhengkun Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Guangdong Shenzhen China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jining China

ISBN: (数字)9789819708857

ISBN: (纸本)9789819708840

Pain is a feedback mechanism the body uses to protect itself. The perception of human pain is still missing in lower limb exoskeleton robots, such as the pain caused by the pressure between the knee joint and the baffle when the lower limb exoskeleton stands up, or the pain caused by the mismatch between the gait and the body function of the wearer when walking. Aiming at the pain perception problem of the exoskeleton robot, this study designed a pressure pain data acquisition paradigm combined first considering the movement mode of the exoskeleton robot, and collected facial electromyography and electrocardiography signals, as well as five levels of pain. Then a deep learning neural Network based on Temporal Convolutional Network and Long Short-Term Memory is designed. The composite Loss of Center Loss, InfoNEC Loss and Softmax Loss is designed. The designed deep neural network model was evaluated using the thermal pain dataset BioVid, and the average recognition rate using only electrocardiography signals reached 86.44%. By Using the fusion signals of electrocardiography, electrocardiogram and electromyogram signals, the average recognition accuracy can reach 87.16%, which is superior to other similar methods, and verifies the effectiveness of the proposed method. The proposed network is also used to verify the collected pressure pain dataset, and the recognition accuracy can reach 87.5%, which proves the validity of the collected data set. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electrocardiography

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Thermal and Magnetic Dual-Responsive Catheter-Assisted Shape Memory Microrobots for Multistage Vascular Embolization

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Research 2024年第3期2024卷 529-543页

作者： Qianbi Peng Shu Wang Jianguo Han Chenyang Huang Hengyuan Yu Dong Li Ming Qiu Si Cheng Chong Wu Mingxue Cai Shixiong Fu Binghan Chen Xinyu Wu Shiwei Du Tiantian Xu Guangdong Provincial Key Lab of Robotics and Intelligent Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina University of Chinese Academy of Sciences BeijingChina Department of Neurosurgery South China HospitalMedical SchoolShenzhen University.ShenzhenChina The Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina.

Catheters navigating through complex vessels,such as sharp turns or multiple U-turns,remain challenging for vascular ***,we propose a novel multistage vascular embolization strategy for hard-to-reach vessels that releases untethered swimming shape-memory magnetic microrobots(SMMs)from the prior catheter to the vessel ***,made of organo-gel with magnetic particles,ensure biocompatibility,radiopacity,thrombosis,and fast thermal and magnetic *** SMM is initially a linear shape with a 0.5-mm diameter at 20°C inserted in a *** transforms into a predetermined helix within 2 s at 38°C blood temperature after being pushed out of the catheter into the *** enable agile swimming in confined and tortuous vessels and can swim upstream using helical propulsion with rotating magnetic ***,we validated this multistage vascular embolization in living rabbits,completing 100-cm travel and renal artery embolization in 2 *** 4 weeks,the SMMs maintained the embolic position,and the kidney volume decreased by 36%.

关键词： turns maintained travel

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Gait recognition based on sEMG and Deep Residual Shrinkage Network

Gait recognition based on sEMG and Deep Residual Shrinkage N...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Luo, Mingxiang Yang, Lijun Sun, Zeyu Yin, Meng Ma, Yue Wu, Xinyu Cao, Wujing Chinese Academy of Sciences and Southern University of Science and Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518005 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch China University of Birmingham United Kingdom

ISBN: (纸本)9798350327182

Transverse resistance exoskeleton is expected to provide better rehabilitation training methods for patients with lower limb injury. Lateral walking gait recognition plays an important role in lateral resistance exoskeleton control. In the phase of lateral walking out of synchrony, the EMG signals produced by the thighs will be different. The EMG signals collected by five subjects while walking laterally were used in the experiment. The four muscles are: the gluteus medius of the left leg, the tensor fascia lata, the adductor major, and the tensor fascia lata of the right leg. Based on the one-dimensional EMG signals of the four muscles, this paper uses the classification model commonly used in the MATlab toolbox for training and recognition. However, the experimental results show that TREE and KNN have poor recognition accuracy for the four gait stages. To this end, this paper applies the convolutional residual shrinkage network (DRSN) to this occasion. The collected one-dimensional EMG signals are plotted as pictures and fed into the model for training and classification. Experimental results show that the classification accuracy is greatly improved compared with the previous model. © 2023 IEEE.

关键词： Muscle

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Towards explainable traffic flow prediction with large language models

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Communications in Transportation Research 2024年第1期4卷 474-490页

作者： Xusen Guo Qiming Zhang Junyue Jiang Mingxing Peng Meixin Zhu Hao Frank Yang Intelligent Transportation Thrust System HubThe Hong Kong University of Science and Technology(Guangzhou)Guangzhou511400China Department of Civil and System Engineering Johns Hopkins UniversityBaltimore21218USA Guangdong Provincial Key Lab of Integrated Communication Sensing and Computation for Ubiquitous Internet of ThingsGuangzhou511400China

Traffic forecasting is crucial for intelligent transportation *** has experienced significant advancements thanks to the power of deep learning in capturing latent patterns of traffic ***,recent deep-learning architectures require intricate model designs and lack an intuitive understanding of the mapping from input data to predicted *** both accuracy and explainability in traffic prediction models remains a challenge due to the complexity of traffic data and the inherent opacity of deep learning *** tackle these challenges,we propose a traffic flow prediction model based on large language models(LLMs)to generate explainable traffic predictions,named *** transferring multi-modal traffic data into natural language descriptions,xTP-LLM captures complex time-series patterns and external factors from comprehensive traffic *** LLM framework is fine-tuned using language-based instructions to align with spatial-temporal traffic flow ***,xTP-LLM shows competitive accuracy compared with deep learning baselines,while providing an intuitive and reliable explanation for *** study contributes to advancing explainable traffic prediction models and lays a foundation for future exploration of LLM applications in transportation.

关键词： Traffic flow predictionLarge language models Spatial-temporal prediction Explainability

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Optimization of a Piezoelectric Bending Beam-based Human Knee Energy Harvester 20

Optimization of a Piezoelectric Bending Beam-based Human Kne...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Liao, Haisu Wang, Yidi Shi, Qiuyu Huang, Ruisen Gao, Fei Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy System

ISBN: (纸本)9798350320831

The concept of extracting energy from the human body to recharge depleted energy sources has gained significant attention. Recently, scientists have focused on harnessing biomechanical energy from the human body while walking. The aim of this study is to optimize a piezoelectric bending beam-based human knee energy harvester to enhance performance. Specifically, the shape of the bending beam (the substrate: a carbon fiber plate) is optimized to modulate the deformation, such that the average strain of the piezoelectric macro fiber composites (MFC) attached to the bending beam is improved to generate more electricity. In addition, the effects of the substrate's thickness and the hinge base's height for the bending beam on the output power are also analyzed. Experimental testing on a subject is conducted to validate our design and test the performance. The harvester generates an average power output of 24.55 mW when walking at 4 km/h on a treadmill. The harvester's total weight is 278g. © 2023 IEEE.

关键词： Energy harvesting

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A Sub-pixel Location Method of Circular PCB Markers Based on Partial Area Effect

A Sub-pixel Location Method of Circular PCB Markers Based on...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Yang, Yingyuan Wang, Xianwen Luo, Sijin Liang, Guoyuan University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China

ISBN: (纸本)9798350327182

With the rapid development of electronic manufacturing industry, automatic optical inspection (AOI) systems are widely applied to mark positioning and defect inspection of printed circuit board (PCB). As the most common mark, the accurate positioning of circle is of great importance in the wiring and assembly of the PCB. Various sub-pixel algorithms have been presented in the past decade. In this paper, we propose an improved version of sub-pixel edge location method based on partial area effect to acquire better sub-pixel points for fitting the circular marks. In stead of the simple one direction offset model, a composite offset model is adopted to diminish the positioning error as much as possible in the case of small gradient differences between horizontal and vertical directions. Besides, the constraints of both gradient magnitude and angle are also introduced for filtering the sub-pixel points at each edge pixel in order to effectively improve the quality of the fitted circle. Experiments conducted on synthetic and real PCB mark images have verified the better performance of the proposed method in terms of anti-interference and location accuracy. © 2023 IEEE.

关键词： Printed circuit boards

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