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IEEE International Conference on Robotics and Biomimetics

作者： Qifan Zhang Jiamin Guo Hui Chai Guoxuan Zhang Zhiyuan Yang Ming Yuan Qin Zhang Yueyang Li Yibin Li School of Control Science and Engineering Shandong University Jinan China Engineering Research Center of Intelligent Unmanned System Ministry of Education Shandong University Jinan China School of Electrical Engineering University of Jinan China

In hazardous explosive disposal scenarios, the autonomous grasping system of quadruped robots demonstrated limited task-level decision-making capabilities and exhibited minimal human-robot interaction (HRI). This paper proposes a task-level intelligent HRI approach, aiming to assist the quadruped robots making multi-object grasping decisions. Following the principle of natural HRI, we design a control terminal equipped with a touch screen. The control terminal receives the video stream from the robot’s primary field of view via a video transmitter. We develop a graphical user interface (GUI) that decodes and displays the image, allowing the operator to interact naturally by touch and select a specific point in the image as the search center point. We employ the shortest Euclidean distance principle, enabling the target recognition module to search around the selected center point. Subsequently, the autonomous grasping system determines the grasping target and initiates the tasks of path planning and grasping detection. Real-world experiments involving multi-target autonomous grasping are conducted to validate the effectiveness of the proposed HRI method and address the challenge of decision making in scenarios with multiple targets. Furthermore, this method can be readily extended to other types of mobile robots.

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Efficient Reinforcement Learning for 3D LiDAR Navigation of Mobile Robot 41

Efficient Reinforcement Learning for 3D LiDAR Navigation of ...

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第41届中国控制会议

作者： Yu Zhai Zhe Liu Yanzi Miao Hesheng Wang China University of Mining and Technology MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic navigation systems exist,they often require extracting semantic information to calculate navigation action,which requires extra modules to provide perceptual information and is not *** propose an end-to-end automatic navigation system based on the reinforcement learning *** particular,the raw 3 D LiDAR data is used to directly map an efficient navigation *** design a novel dense reward function to handle the reward sparsity issue and provide a graphical representation method to enable the efficient feature learning from the raw 3 D LiDAR data in our navigation *** addition,an imitation learning based policy initialization is introduced before the subsequent reinforcement learning,which increases the learning efficiency and,in the meantime,still encouraging the robot to explore all the potential states to achieve advanced performance than the imitated *** navigation model is trained in the Webots environment and the experimental results show that our model has efficient and flexible navigation performance in complex *** importantly,trained model can be easily extended to unfamiliar environments.

关键词： End-to-end Navigation Mobile robot Reinforcement Learning 3D LiDAR

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An Encoder-Free Joint Velocity Estimation Method for Serial Manipulators Using Inertial Sensors

An Encoder-Free Joint Velocity Estimation Method for Serial ...

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2021 IEEE International Conference on Robotics and Automation, ICRA 2021

作者： Xu, Xiaolong Sun, Yujie Tian, Xincheng Zhou, Lelai Li, Yibin The Center for Robotics School of Control Science and Engineering Shandong University Jinan250061 China The Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan250061 China

ISBN: (纸本)9781728190778

This paper focuses on developing a real-time and flexible velocity estimation approach for serial revolute manipulator using only one inertial measurement unit (IMU) mounted on each link side of the manipulator. Particularly, the proposed approach has no requirement for the installation position and orientation of the IMU, which improves the flexibility of the implementation procedure. A joint velocity model is established based on the proposed principle of constructing coordinate system according to the robotic geometric information. The general solutions are derived in detail, thereby the proposed algorithm can be generalized into any other robots with the same geometric configuration. With the method, the joint rotational velocity measurements of static and dynamic robotic motion are provided compared to encoders. Experimental results based on the six degrees of freedom (DOF) collaborative manipulator have validated the feasibility and effectiveness of the proposed approach. The proposed method has the benefits of low cost and flexibility, which could work as a redundant velocity monitor criterion to provide assistant joint velocity measurements. © 2021 IEEE

关键词： Velocity measurement

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Enhancing Autism Spectrum Disorder Early Detection with the Parent-Child Dyads Block-Play Protocol and an Attention-enhanced GCN-xLSTM Hybrid Deep Learning Framework

arXiv

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arXiv 2024年

作者： Li, Xiang Fan, Lizhou Wu, Hanbo Chen, Kunping Yu, Xiaoxiao Che, Chao Cai, Zhifeng Niu, Xiuhong Cao, Aihua Ma, Xin School of Control Science and Engineering Shandong University Shandong Jinan250061 China Engineering Research Center of Intelligent Unmanned System Shandong University Shandong Jinan250061 China School of Information University of Michigan Ann Arbor48109 United States Department of Pediatrics Qilu Hospital of Shandong University Shandong Jinan250061 China

Autism Spectrum Disorder (ASD) is a rapidly growing neurodevelopmental disorder. Performing a timely intervention is crucial for the growth of young children with ASD, but traditional clinical screening methods lack objectivity. This study introduces an innovative approach to early detection of ASD. The contributions are threefold. First, this work proposes a novel Parent-Child Dyads Block-Play (PCB) protocol, grounded in kinesiological and neuroscientific research, to identify behavioral patterns distinguishing ASD from typically developing (TD) toddlers. Second, we have compiled a substantial video dataset, featuring 40 ASD and 89 TD toddlers engaged in block play with parents. This dataset exceeds previous efforts on both the scale of participants and the length of individual sessions. Third, our approach to action analysis in videos employs a hybrid deep learning framework, integrating a two-stream graph convolution network with attention-enhanced xLSTM (2sGCN-AxLSTM). This framework is adept at capturing dynamic interactions between toddlers and parents by extracting spatial features correlated with upper body and head movements and focusing on global contextual information of action sequences over time. By learning these global features with spatio-temporal correlations, our 2sGCN-AxLSTM effectively analyzes dynamic human behavior patterns and demonstrates an unprecedented accuracy of 89.6% in early detection of ASD. Our approach shows strong potential for enhancing early ASD diagnosis by accurately analyzing parent-child interactions, providing a critical tool to support timely and informed clinical decision-making. © 2024, CC BY-NC-ND.

关键词： Diseases

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Vehicle Tracking Method Based on Attention-YOLOv5 and Optimized DeepSort Models 11

Vehicle Tracking Method Based on Attention-YOLOv5 and Optimi...

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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Li, Zhuang Tian, Xincheng Liu, Yan Shi, Xiaorui Shandong University Center for Robotics School of Control Science and Engineering Jinan250061 China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan250061 China Sinotruk Jinan Power Co. Ltd. Sinotruk Industry Park Zhangqiu Jinan250220 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Vehicle tracking plays a vital role in traffic management and autonomous driving. In order to further improve the accuracy of vehicle tracking, reduce the number of ID-Switch and enhance the anti-interference ability to the outside world, we propose a vehicle detection and tracking model based on Attention-YOLOv5 and optimized DeepSort. Firstly, YOLOv5 with attention mechanism was used as the front-end target detector, that is, add CBAM and ECA attention mechanisms to the backbone network of the benchmark YOLOv5 separately to improve the feature extraction ability. Then use the transfer learning idea to train it on the BDD dataset, it is concluded that ECA-YOLOv5 has the highest detection accuracy. Further we optimize the DeepSort algorithm, in order to overcome the disadvantages of the pre-training model not targeting traffic vehicles, we improve the re-recognition network structure and optimize the VeRi re-identification dataset, next perform re-identification pre-training on the Improved-VeRi dataset based on transfer learning. In order to make the vehicle features evenly distributed around the center of the class and improve feature resolution, a loss function L/CL combining the Softmax loss function and center loss function is proposed. In the experimental part, collecting some highway traffic videos of different scenes. At first, conduct visual analysis, then perform ablation experiments, and evaluate by using MOTA, MOTP and ID-Switch. Compared with the benchmark algorithm, the tracking performance is significantly improved. © 2022 IEEE.

关键词： Benchmarking

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Interaction between internal solitary waves and the seafloor in the deep sea

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Deep Underground Science and engineering 2024年第2期3卷 149-162页

作者： Zhuangcai Tian Jinjian Huang Jiaming Xiang Shaotong Zhang Jinran Wu Xiaolei Liu Tingting Luo Jianhua Yue State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and TechnologyXuzhouChina Research Center for Deep Ocean Science and Underwater Engineering China University of Mining and TechnologyXuzhouChina Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Lab of Submarine Geosciences and Prospecting TechniquesMOECollege of Marine GeosciencesOcean University of ChinaQingdaoChina Institute for Learning Sciences&Teacher Education Australian Catholic UniversityBrisbaneQueenslandAustralia Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering Ocean University of ChinaQingdaoChina Department of Chemical and Biomolecular Engineering National University of SingaporeSingaporeSingapore School of Resources and Geosciences China University of Mining and TechnologyXuzhouChina

Internal solitary wave(ISW),as a typical marine dynamic process in the deep sea,widely exists in oceans and marginal seas *** interaction between ISW and the seafloor mainly occurs in the bottom boundary *** the seabed boundary layer of the deep sea,ISW is the most important dynamic *** study analyzed the current status,hotspots,and frontiers of research on the interaction between ISW and the seafloor by *** on the action of ISW on the seabed,such as transformation and reaction,a large amount of research work and results were systematically analyzed and *** this basis,this study analyzed the wave–wave interaction and interaction between ISW and the bedform or slope of the seabed,which provided a new perspective for an in‐depth understanding of the interaction between ISW and the ***,the latest research results of the bottom boundary layer and marine engineering stability by ISW were introduced,and the unresolved problems in the current research work were *** study provides a valuable reference for further research on the hazards of ISW to marine engineering geology.

关键词： bottom boundary layer interaction internal solitary wave seafloor sediment

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Voltage control for Black-Start Based on Energy Storage Station and Wind Farm

Voltage Control for Black-Start Based on Energy Storage Stat...

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intelligent Power and systems (ICIPS), International Conference on

作者： Yuanzhen Zhu Xinyu Wei Tianshu Li Yiheng Chen Ning Zhou Qiao Fang Kang Zhao Runjia Sun Shandong Smart Grid Technology Innovation Center State Grid Shandong Electric Power Company Electric Power Science Research Institute Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Jinan China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

Energy storage station (ESS) and wind farm (WF) have the potential to serve as a black-start sources to accelerate the power system restoration after blackout. However, the voltage security problem when start the auxiliary machines of power plants limit their reliability as black-start sources. A voltage control method is proposed for ESS and WF combined black-start sources to improve the voltage security during black-start. Firstly, the black-start process based on grid-forming ESS and WF is presented, and the voltage control framework is established. Then, a predictive control method considering the impact of active power on voltage variations is proposed, in which different optimization modes are established to obtain the active and reactive control sequences for WF and ESS. Finally, black-start simulation with Matlab/Simulink demonstrate the proposed method can improve the voltage security level when starting auxiliary machines of power plants.

关键词： Simulation Wind farms Regulation Security Reliability Voltage control Power generation Predictive control Grid forming Energy storage

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Spatial Pyramid Attention Based Two-Stream Network for Fish Behavior Recognition

Spatial Pyramid Attention Based Two-Stream Network for Fish ...

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Chinese Automation Congress (CAC)

作者： Hao Zhang Xin Ma Yining Yu Liang Wang Lin Hao Center for Robotics School of Control Science and Engineering Shandong University Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Shandong Marine Group Ltd Jinan China Shandong Deep Sea Green Farming Ltd Qingdao China

In intensive aquaculture, achieving accurate monitoring of fish behavior is crucial for improving efficiency. Previous studies on fish behavior recognition have been limited to recognizing fish school behavior from a global perspective, disregarding the importance of recognizing behaviors that occur in local regions. In this study, a spatial pyramid attention based two-stream network (SPA-TSN) is proposed to recognize fish behavior from both global and local perspective. SPA-TSN is comprised of a spatial stream and a motion stream, both of which use a spatial pyramid attention module to obtain the spatial and temporal features of fish behavior respectively. Specifically, the spatial pyramid attention module aggregates the features from different levels of the baseline to capture the correlation between local and global information. Then, a fusion feature is obtained by adding the temporal feature to the spatial feature. The three features are assigned different weights through a learnable multiplier $M$ for behavior recognition. To validate the effectiveness of the proposed method, experiments are conducted on our established fish behavior dataset which consists four common fish behaviors. The results demonstrate that the proposed method has the best performance with an accuracy of 95.904%, performing better than state-of-the-art methods.

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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

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IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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