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

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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Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios With Multiagent Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 317-326页

作者： Liu, Weiwei Hu, Wenxuan Jing, Wei Lei, Lanxin Gao, Lingping Liu, Yong Zhejiang University The Advanced Perception on Robotics and Intelligent Learning Lab College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang 310027 China Alibaba DAMO Academy Autonomous Driving Lab Zhejiang 311121 China Huzhou University College of Information Engineering Zhejiang 313000 China

Autonomous vehicles trained through multiagent reinforcement learning (MARL) have shown impressive results in many driving scenarios. However, the performance of these trained policies can be impacted when faced with diverse driving styles and personalities, particularly in highly interactive situations. This is because conventional MARL algorithms usually operate under the assumption of fully cooperative behavior among all agents and focus on maximizing team rewards during training. To address this issue, we introduce the personality modeling network (PeMN), which includes a cooperation value function and personality parameters to model the varied interactions in high-interactive scenarios. The PeMN also enables the training of a background traffic flow with diverse behaviors, thereby improving the performance and generalization of the ego vehicle. Our extensive experimental studies, which incorporate different personality parameters in high-interactive driving scenarios, demonstrate that the personality parameters effectively model diverse driving styles and that policies trained with PeMN demonstrate better generalization than traditional MARL methods. © 2007-2012 IEEE.

关键词： Reinforcement learning

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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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Walking Control for a Self-Balancing Exoskeleton on Flat Ground

Walking Control for a Self-Balancing Exoskeleton on Flat Gro...

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

作者： Li, Jinke Tian, Dingkui Li, Feng Sun, Jianquan Yin, Meng Wu, Xinyu University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Siat Cuhk Joint Laboratory of Robotics and Intelligent Systems China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

Designed to provide rehabilitation or the assistance of walking for individuals who are with lower limb muscle injuries or spinal during their activities, self-balancing lower limb exoskeletons have been developed. This paper introduces an innovative controller for a fully actuated exoskeleton that ensures stable walking for wearers without the need for external devices. The exoskeleton robot is represented as a center of mass model, and based on this representation, the trajectory generation and controller are discussed, aiming to improve locomotion stability. To assess the stability and dynamic performance, a stable walking experiment with the exoskeleton was conducted, involving a male subject. © 2023 IEEE.

关键词： Exoskeleton (robotics)

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SigmoidGS: To Guide Depth More Effectively

SigmoidGS: To Guide Depth More Effectively

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chow, Hongai Shen, Licheng Wang, Lingyun Zhang, Tong Wang, Mengqiu Han, Yuxing Shenzhen International Graduate School Tsinghua University Shenzhen China Zero-Zero Lab Zero-Zero Robotics Inc. Hangzhou China Advanced Technology Institue Zhejiang University Hangzhou China

ISBN: (纸本)9798350368741

The recent success of 3D Gaussian Splatting (3DGS) on the task of novel view synthesis has amazed every one with its photorealistic results with high training and rendering speed. This paper aims to increase the interpretability of the model in both geometric attribute and appearances by a simple yet effective method: lifting constraints on color features of each splat. This enables more accurate guidance from monocular depth prediction models and strengthen the ability of model to reconstruct scene geometry. Experiments shows that this effectively reduces indeterminacy of the reconstruction problem and allows better understanding of the scene structure and individual, especially in scenes with limited viewpoints, while maintaining high-fidelity rendering even in some of the uncovered views. © 2025 IEEE.

关键词： 3D reconstruction Gaussian Splatting Neural Radiance Field Neural Rendering Novel View Synthesis

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Adaptive Adjustment of Factor's Weight for a Multi-Sensor SLAM 2

Adaptive Adjustment of Factor's Weight for a Multi-Sensor SL...

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2022 2nd International Conference on Computer, Internet of Things and Control Engineering, CITCE 2022

作者： Zhu, Zihan Zhang, Yi Wang, Weijun Feng, Wei Luo, Haowen Zhang, Yaojie Shenzhen Institute of Advanced Technology Chinese Academy of Sciences 518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Lab of Construction Robotics and Intelligent Manufacturing Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial International Joint Research Center for Robotics and Intelligent Construction Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

A multi-sensor fusion simultaneous localization and mapping(SLAM) method based on factor graph optimization that can adaptively modify the weight of the graph factor is proposed in this study, to enhance the localization and mapping capability of autonomous robots in tough situations. Firstly, the algorithm fuses multi-lines lidar, monocular camera, and inertial measurement unit(IMU) in the odometry. Second, the factor graph is constructed using lidar and visual odometry as the unary edge and binary edge constraints, respectively, with the motion determined by IMU odometry serving as the primary odometry in the system. Finally, different increments of IMU odometry, lidar odometry and visual odometry are computed as favor factors to realize the adaptive adjustment of the factor's weight. The suggested method has greater location accuracy and a better mapping effect in complex situations when compared to previous algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Optical radar

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Design and Development of IoT Based Weather and Air Quality Monitoring Station

Design and Development of IoT Based Weather and Air Quality ...

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2023 International Conference on robotics and Automation in Industry, ICRAI 2023

作者： Haris, Muhammad Ubaid, Bilal Bibi, Uzma Said, Ameer Us Saqib, Syed Najm Khan, Shahbaz Tufail, Muhammad Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan Institute of Manufacturing Engineering Management University of Engineering and Applied Sciences Swat Swat Pakistan

ISBN: (纸本)9781665464727

This paper presents the Design and Development of IoT Based Weather and Air Quality Monitoring stations that provide weather-related information for agriculture, and aviation climate forecasting purposes. The prototype is made up of an outdoor unit that consistently monitors numerous climatic variables such as temperature, humidity, barometric pressure, wind speed, wind direction, rainfall, and air quality using sensors with high accuracy. The air quality index(AQI) is also calculated using the sensors values which tell us whether the atmosphere is safe or polluted. ESP32(Microcontroller) which has a WiFi module is used to gather and send the sensor data through the Internet of things (IoT) to a ThingSpeak channel (IoT cloud), an internet platform where the data is saved, analyzed and read the data remotely. The weather station makes use of photovoltaic power and a rechargeable lead-acid battery to sustain the system. This paper also discusses the obvious strengths and shortcomings of the system and suggests plausible upgrades to assist the system in obtaining higher and long-term performance. © 2023 IEEE.

关键词： Internet of things

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Artificial Marker-Aided Localization for Service Robots in Visually Repetitive Environments

Artificial Marker-Aided Localization for Service Robots in V...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： DongKi Noh Jeongsik Choi Seungmin Baek Advanced Robotics Lab. CTO Division LG Electronics Seoul Republic of Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

In recent years, simultaneous localization and mapping (SLAM) has emerged as a critical technique for enabling the autonomous capabilities of service robots. However, practical SLAM applications often face significant performance challenges in visually and geometrically repetitive environments, which impede accurate localization. To address these challenges and ensure reliable localization for service robots, this work utilizes artificial markers, specifically AprilTags and ArUco tags. This paper presents a method that strategically leverages these markers, using them in minimal quantities while maximizing their localization impact. By leveraging the Kimera-VIO and TagSLAM algorithms, the proposed approach offers several contributions: (a) consistent pose estimation through a lightweight pose-graph optimizer suitable for resource-constrained systems; (b) an efficient strategy for optimizing the placement of artificial markers within target environments; and (c) validation of the proposed method in real-world environments, including warehouses and offices, using a commercially available service robot. This approach provides a viable industrial solution for improving localization performance in commercial service robots.

关键词： Location awareness Performance evaluation Simultaneous localization and mapping Service robots Semantics Pose estimation Reliability Faces Consumer electronics Logistics

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A Fault-tolerant Control Method for USV Trajectory-tracking with Sensor Faults

A Fault-tolerant Control Method for USV Trajectory-tracking ...

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

作者： Guo, Weilun Li, Weimin Wu, Xinyu Wang, Haibin Mu, Xinxing Wang, Qiang Xu, Yi Shandong Zhongke Advanced Technology Co. Ltd Jinan250098 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China

ISBN: (纸本)9798350327182

This paper studies the trajectory tracking problem of the unmanned surface vehicle with sensor deviation faults. Firstly, the trajectory tracking controller based on model predictive control is designed according to the physical characteristics of the unmanned vehicle system. Moreover, an event trigger mechanism is explored in the controller to reduce the waste of computing resources. Then, a H∞ fault estimator is designed to accurately estimate the value of sensor deviation faults. Finally, the influence of sensor faults on the designed controller is analyzed. At the same time, the faults information was used for improving the tracking performance. The proposed trajectory tracking method with the fault-tolerant algorithm is verified by simulation examples. © 2023 IEEE.

关键词： Controllers

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