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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Ru, Jingyu Hao, Dongqiang Yu, Shuangjiang Liu, Hao Xu, Hongli Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China School of Information Science and Engineering Northeastern University Shenyang110819 China

ISBN: (纸本)9789811694912

Cooperative detection of fixed detection sequence positions in complex underwater areas through multi-agent combination is an indispensable means to complete special underwater detection tasks. Studying the scheduling and matching underwater robot resources to meet the requirements of environmental detection tasks under the conditions of meeting task and detection requirements is a research hotspot in the field of multi-agent task allocation. In traditional task allocation process, the detection dimension is single, and the fixed detection sequence is disre garded. This work proposes a novel multidimensional resource scheduling allocation algorithm (CR-C-NSPSO) for heterogeneous agents based on improved NSPSO. The algorithm is composed of a solution set conflict resolution algorithm and a collision optimization strategy module. It can establish a mathematical expression model that meets the needs of a fixed sequence of tasks and builds a solution space for each task while resolving the needs of task conflicts in the same time and space. On the basis of meeting the task priority, the impact of resource scheduling and allocation conflicts caused by optimized search is weakened. Finally, simulations verify the feasibility and effectiveness of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Dynamic Event-Triggered H∞ Sliding Mode Control for Multi-Agent Systems Using a Dual Hidden Markov Model

Dynamic Event-Triggered H∞ Sliding Mode Control for Multi-A...

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Chinese Automation Congress (CAC)

作者： Ying Zheng Huixia Cui Junyi Wang College of Information Science and Engineering Northeastern University Shenyang China Faculty of Robot Science and Engineering Northeastern University Shenyang China Faculty of Robot Science and Engineering Foshan Graduate School of Innovation Northeastern University Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

This paper investigates the dynamic event-triggered $H$ ∞ sliding mode control (SMC) issue for a class of linear multi-agent systems (MASs) with Markov jump parameters and Markov switching topologies. A mapping technique for continuous-time Markov chains is employed to address the challenge of MASs with dual Markov jumping process. Based on the hidden Markov model detector, the distributed event-triggered $H$ ∞ sliding mode controllers are constructed, and the dynamic event-triggering scheme (DETS) is introduced to reduce bandwidth pressure. By constructing mode-dependent Lyapunov- Krasovskii functionals (LKFs), the stochastic consen-sus conditions of MASs with prescribed $H$ ∞ performance index are formulated by linear matrix inequalities (LMIs). Finally, a numerical simulation is conducted to validate the effectiveness of the proposed method.

关键词： Event detection Hidden Markov models Process control Switches Numerical simulation Topology Performance analysis Sliding mode control System analysis and design Multi-agent systems

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Review of Supernumerary robotic Limbs 2

Review of Supernumerary Robotic Limbs

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2nd International Conference on robotics, Automation and Intelligent Control, ICRAIC 2022

作者： Zhang, Kailing Long, Yi Luo, Xiaofeng College of Information Science and Engineering Northeastern University Shenyang Liaoning China Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China Foshan Graduate School of Innovation Northeastern University Guangdong Foshan China

Supernumerary robotic limbs (SRLs) are the expansion of human body. It can provide extra limbs to enhance human ability. It is a novel way to assist the existing limbs using SRLs without prejudice to the normal activities of the user's arm. It has great application prospects in the fields of military, industry, rehabilitation training and assistance in daily life. Based on the public research results of SRLs around the world, the development state of SRLs are summarized from the mechanical architecture, actuation mode, motion intention prediction and control strategy. The technical problems for SRLs are analyzed and their future technical development is given. © Published under licence by IOP Publishing Ltd.

关键词： robotics

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The Transfer Learning Method for Reducing the Influence of Electrode Shift 13

The Transfer Learning Method for Reducing the Influence of E...

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2023

作者： Gao, Shaoqing Wen, Shiguang Ren, Chuanjian Liu, Jing Wu, Qi Han, Lu Wang, Fei Northeastern University Faculty of Information Science and Engineering LiaoNing ShenYang110167 China Northeastern University Faculty of Robot Science and Engineering LiaoNing ShenYang110167 China College of Information Science and Engineering Northeastern University LiaoNing ShenYang110167 China LiaoNing Disabled Person's Service Center LiaoNing Shen Yang China

ISBN: (纸本)9798350315196

In systems based on pattern recognition using surface electromyography (sEMG) signals, there exists a problem of electrode shift during the process of donning and doffing. Directly using models trained on the source domain may result in limited prediction ability and a decrease in recognition accuracy. In this paper, a Domain-Adversarial Neural Networks(DANN) network is constructed based on CNN RES and the last layer of the feature extraction network and label predictor is fine-tuned. The experimental dataset used in the study was SeNic-main, proposed by the Shenyang Institute of Automation, Chinese Academy of sciences. The experimental results were compared with the baseline network CNN-RES(CNN-ResNet), and eight tests were conducted on data with offsets of 10 degrees and -10 degrees. The results showed that the average testing accuracy was increased by 15.47% and 13.96% respectively, compared to CNN-RES. © 2023 IEEE.

关键词： Electrodes

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OFSLMs: Offline Fine-Tuned Small Language Models Based on Hybrid Synthetic Knowledge for robot Introspective Decision-Making

OFSLMs: Offline Fine-Tuned Small Language Models Based on Hy...

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IEEE International Conference on robotics and Biomimetics

作者： Jinbiao Zhu Lishan Wang Yi Guc Fei Wang Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning Province China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

The combination of robots with large language models (LLMs) offers the potential to create more intelligent systems, a prospect that has garnered attention from researchers in recent years. Current efforts primarily focus on constructing prompt systems through online APIs and high-level natural language-based planning and decision-making offline. However, these approaches often neglect scenarios with weak network connectivity and downplay the close integration between models and the robot's lower-level control. We propose that robots should be equipped with Offline Fine-tuned Small Language Models (OFSLMs) capable of generating introspective decisions offline. To this end, we design a workflow for creating these OFSLMs and develop a hybrid synthetic fine-tuning dataset with human and GPT-4's annotation. This dataset contains 2,663 cases to train and evaluate OFSLMs to generate “plan” and lower-level control codes called “solution” based on given “instruction.” Additionally, we devise a two-stage evaluation method to select the best OFSLMs. In experiments, we analyze the distribution of the dataset, and then we select the recent 9 open-source small language models and filter out the best 3 models using proposed workflow. We further perform nonlinear fitting on these OFSLMs' numerical metrics, and explore the generalization capabilities of the OFSLMs. Experiments demonstrate that the dataset we create is semantically rich and that our proposed workflow yields high-quality OFSLMs. These models exhibit non-linear growth in metrics. Moreover, our OFSLMs demonstrate the ability to perform offline robot decision-making and generate control code, highlighting their specialization; simultaneously, OFSLMs also show comparable performance in non-decision-related text-based question-answering tasks, indicating their generalization capability.

关键词： Measurement Analytical models Codes Annotations Decision making Fitting Real-time systems Numerical models robots Synthetic data

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Design and Control of a Quasi-direct Drive Actuated Knee Exoskeleton

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Journal of Bionic engineering 2022年第3期19卷 678-687页

作者： Yi Long Yajun Peng Foshan Graduate School of Northeastern University Foshan528000China Faculty of Robot Science and Engineering Northeastern UniversityShenyang110000China Zhongshan Walkbest Intelligent Medical Device Co.Ltd Zhongshan528400China

This paper describes the design and control of a portable and lightweight knee exoskeleton for people with knee *** knee exoskeleton is designed based on our custom quasi-direct drive actuation composed of a DC motor unit and a transmission mechanism encompassing three *** online gait generation method based on gait step calculation and direct measurement using Inertial Measurement Unit(IMU)sensors is proposed to provide continuous assistance during *** on the generated gait trajectory online,Active Disturbance Rejection Control(ADRC)incorporating the feedforward compensation approach is proposed to help the human leg move in consideration of external *** developed knee exoskeleton has been employed successfully to assist impaired users with knee dysfunction to walk in a health recovery *** experimental results indicate that the online gait generation method and the proposed control method are suitable for the knee *** maximum value of the target knee angular position is approximately 50°and the mean of the control torque for the knee joint is located in the interval of[−2 Nm,4 Nm].The developed knee exoskeleton has the potential to regain normal gait to improve strength and endurance during walking in their activities of daily life.

关键词： Exoskeleton Knee dysfunction Quasi-direct drive Active disturbance rejection control Gait generation

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Utilizing Large Language Models Enhanced by Chain-of-Thought for the Diagnosis of Typical Medical Cases 10th

Utilizing Large Language Models Enhanced by Chain-of-Though...

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10th China Health Information Processing Conference, CHIP 2024

作者： Liu, Jiqiang Liu, Chenyang Faculty of Robot Science and Engineering Northeastern University Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9789819642977

In the past two years, the large language model has set off a new wave of research in the field of natural language processing, showing the ability of general-purpose artificial intelligence, which has been widely concerned by the industry. With the rapid development of medical vertical large model, its potential in clinical application has been paid more and more attention. However, there are gaps in the diagnosis of typical medical records. In order to continuously improve the application effect of medical large model in actual clinical scenarios and accelerate the implementation of medical large model, this paper describes the specific situation of our participation in the 10th China Conference on Health Information Processing (CHIP 2024). We used the improved LoRA method for fine tuning, and then used the Chain-of-Thought method for post-processing in the reasoning stage to improve performance. The experimental results show that the F1 score of our method in the final second round of evaluation reaches 0.9356, ranking second, which effectively verifies the generalization and robustness of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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An Asynchronous SSVEP-BCI for Intelligent Rehabilitation Exoskeleton Based on Alpha Rhythm-Detected CCA 13

An Asynchronous SSVEP-BCI for Intelligent Rehabilitation Exo...

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2023

作者： Sun, Jintao Wen, Shiguang Wen, Yongzhao Liu, Jing Wu, Qi Han, Lu Wang, Fei College of Information Science and Engineering Northeastern University Liaoning Shenyang110167 China Northeastern University Faculty of Robot Science and Engineering Liaoning Shenyang110167 China LiaoNing Disabled Persons' Service Center Liaoning Shenyang China

ISBN: (纸本)9798350315196

Although great progress has been made in the research on rehabilitation exoskeletons based on steady-state visually evoked potential (SSVEP)-based brain-computer interface (BCI), some factors that limit the practical applications of rehabilitation exoskeletons based on BCIs still exist. On the one hand, traditional SSVEP-BCI uses the computer screen (CS) to generate visual stimuli, which leads to poor portability, on the other hand, most BCIs are in a synchronous mode, which prevents users from autonomously controlling the system. To overcome these two problems, augmented reality (AR) technology is introduced to generate the visual stimuli, and an asynchronous control method based on the blocking phenomenon of alpha waves is proposed in this study. The offline experiment is designed to determine the classification threshold of the idle state and control state and compare the different performances of SSVEP-BCI with and without an AR environment. Finally, an intelligent rehabilitation exoskeleton platform is used for online validation. Results of the online experiment indicate that all subjects could control the rehabilitation exoskeleton to complete the rehabilitation tasks, which indicates the applicability of the intelligent rehabilitation exoskeleton system and improves the potential for application of the rehabilitation exoskeleton based on BCI. © 2023 IEEE.

关键词： Brain computer interface

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Expansive Spatial-Temporal Kernel Convolution Network for Skeleton-Based Action Recognition

Expansive Spatial-Temporal Kernel Convolution Network for Sk...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Ziao Li Junyi Wang Quan Zhou Chengda Li Faculty of Robot Science and Engineering Northeastern University Shenyang China Faculty of Robot Science and Engineering Foshan Graduate School of Innovation Northeastern University China

In skeleton-based action recognition, graph convolutional networks (GCNs) have become the most common method due to their strong modeling ability on graph data and the utilization of prior knowledge on human skeleton. However, convolutional methods have been overlooked in this field despite their wide applications in visual tasks, mature libraries, and learning resources. In this paper, we propose an Expansive Spatial-Temporal Kernel Convolution Network (ESTCN) consisting of Expansive Spatial Kernel Convolution and Expansive Temporal Kernel Convolution for spatial feature extraction. Our ESTCN adopts large kernel convolution to achieve global receptive field and utilize prior knowledge on human joints. Extensive experiments on NTU-RGB+D dataset demonstrate that our method achieves comparable performance with GCN-based methods and outperforms other convolutional methods.

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Intelligent interaction system based on multimodal conformal triboelectric nanogenerator patch for disabled sports and life

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science China(Technological sciences) 2025年第2期68卷 290-305页

作者： Yuzhang WEN Mengqi ZHANG Zhenning XIE Zida AN Bing LIU Fengxin SUN Tianming ZHAO Zuojun YU Fei WANG Yupeng MAO Physical Education Department Northeastern UniversityShenyang 110819China Faculty of Robot Science and Engineering Northeastern UniversityShenyang 110819China China Ice Sports College Beijing Sport UniversityBeijing 100084China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Criminal Investigation Police University of China Shenyang 110035China

Intelligent interaction technology based on advanced sensing units has become a research *** this paper,an intelligent interaction system(IIS)based on a multimodal conformal triboelectric nanogenerator patch(MCTP)is reported for sports monitoring and life promotion of the *** IIS consists of a cloud-based smart sports recognition program and a smart life *** porous micro-reinforced structure of polyurethane(PU)Sponge&Ecoflex,and the surface modification of PTFE by coating it with MXene endows the MCTP with excellent electrical *** shows good angle and force sensitivities of 1.1 V/°and 1.61 V/N,respectively,and has an ultra-fast response time of 15 ms,meeting the needs of human motion *** MCTP can also capture the mechanical energy,producing a maximum output power of 139μ*** with the commercial inertial measuring unit(IMU),the MCTP shows better consistency in human joint angle sensing.A precise analysis of wheelchair curling sports monitoring points is achieved by combining the MCTP and the human anatomy *** cloud-based smart sports recognition program utilizes machine learning to achieve visual feedback on the three throwing technologies of draw,takeout and *** addition,the developed smart life application uses a highsensitivity MCTP-sensor array design to achieve a variety of smart home interactions through simple finger ***,the IIS integrates the three major functions of smart sports sensing,energy capture,and smart home control,providing important application prospects in the fields of smart sports and human-computer interaction for the disabled.

关键词： triboelectric nanogenerator machine learning smart sports smart home human-computer interaction

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