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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zheng, Liangsheng Ma, Yue Li, Mengyao Xiao, Yang Feng, Wei Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781665436786

Motor imagery brain-computer interface system based on Electroencephalogram (EEG) is an effective way to help the disabled recover part of their motor abilities. However, decoding the movement intention contained in the EEG signal accurately presents many challenges. In this paper, we propose a time-frequency decomposition-based weighted ensemble learning (TFDWEL) method, which aims to improve the classification performance of motor imagery EEG signals. The TFDWEL method divides the EEG signal into multiple subsets, and uses four time-frequency processing methods to extract the time-frequency sub-bands of each subset. Then the feature extraction model and classifier model of each subset trained by the common spatial pattern (CSP) algorithm and the support vector machine (SVM) algorithm are used to build a set of base learners. The least square error estimation method is used to learn the weight of each base learner, and finally the weighted summation method is used to obtain the final decision. The classification performance of the TFDWEL method is evaluated on the BCI Competition IV Data Set 2b, and the results show that the classification accuracy of 81.58% can be obtained. Superior classification performance indicates that the TFDWEL method can be used in further research to help the rehabilitation of the disabled. © 2021 IEEE.

关键词： Electroencephalography

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A smart wearable device for capturing biomechanical energy from human knee motion

A smart wearable device for capturing biomechanical energy f...

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IEEE/ASME (AIM) International Conference on advanced intelligent Mechatronics

作者： Hugo Hung-Tin Chan Haisu Liao Xuan Zhao Junrui Liang Wei-Hsin Liao Xinyu Wu Fei Gao Guangdong Provincial Key Laboratory 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 Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China School of Information Science and Technology ShanghaiTech University Shanghai China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Sustainable power supply is a challenge for portable and wearable electronic devices such as cell phones and headsets. To address this, researchers proposed capturing biomechanical energy from human motion to generate electricity. This paper proposed and developed a lightweight wearable device to capture the biomechanical energy from the human knee motion. To reduce the effect of inertial force on human gait, we developed a lightweight and compact transmission chain to convert the bidirectional rotation of the knee to a unidirectional rotation of the generator. Two input bevel gears with opposite one-way bearings on the same shaft are engaged with a single output bevel gear of the generator thereby only one input bevel gear is engaged for each input direction, achieving unidirectional output. In addition, to reduce velocity fluctuation and further minimize the effect of inertial force, a flywheel was fixed to the motor shaft via a gearbox. A prototype of the wearable device was developed and tested on a subject walking on a treadmill. Experimental results shows the flywheel enabled the harvester to achieve a continuous output while halving voltage fluctuations compared to a conventional harvester. The harvesters average power output can reach 0.11 W with minimal effects on the subject’s walking gait.

关键词： Knee Legged locomotion Biomechanics Shafts Fluctuations Voltage fluctuations Torque

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High Sensitivity Submicron Scale Temperature Sensor Based on Perovskite Nanoplatelet Lasers

SSRN

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SSRN 2024年

作者： Zhao, Ruofan Tao, Jianxun Xi, Yuying Chen, Jiangzhao Ji, Ting Wang, Wenyan Wen, Rong Cui, Yanxia Chen, Junsheng Lia, Guohui College of Physics and Optoelectronics Key Laboratory of Interface Science and Engineering in Advanced Materials Key lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China School of Materials Science and Engineering Kunming University of Science and Technology Kunming650093 China Shanxi-Zheda institute of advanced materials and chemical engineering China Nano-Science Center Department of Chemistry University of Copenhagen Universitetsparken 5 CopenhagenDK-2100 Denmark

Submicron scale temperature sensors are crucial for a range of applications, particularly in micro and nanoscale environments. One promising solution involves the use of active whispering gallery mode (WGM) microresonators. These resonators can be remotely excited and read out using free-space structures, simplifying the process of sensing. In this study, we present a submicron-scale temperature sensor with a remarkable sensitivity up to 190 pm/℃ based on a triangular CH3NH3PbI3 nanoplatelet (NPL) laser. Notably, as temperature changes, the peak wavelength of the laser line shifts linearly. This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser. The optical modes are confined within the perovskite NPL, which measures just 85 nanometers in height, due to total internal reflection. Our NPL laser boasts several key features, including a high Q-factor of ~ 2610 and a low laser threshold of about 19.8 µJ cm−2. The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors. This advancement paves the way for significant progress in the development of ultrasmall temperature sensors, opening new possibilities across various fields. © 2024, The Authors. All rights reserved.

关键词： Perovskite

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Discrete Element Simulation of Durability for Bionic Wheels of Mars Rover 2

Discrete Element Simulation of Durability for Bionic Wheels ...

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2nd Spring International Conference on Defence technology, ICDT 2020

作者： Lin, Y.C. Yan, Y.P. Yuan, B.F. Liu, Y.F. Zou, M. Beijing Key Laboratory of Intelligent Space Robotic System Technology and Application Institute of Spacecraft System Engineering CAST Beijing100094 China Key Laboratory for Bionics Engineering of Education Ministry Jilin University Changchun130022 China

Four kinds of bionic surfaces (convex, scale-like, ribbed and concave shape) for Mars rover wheels were designed to improve wheel durability. A discrete element wheel-soil simulation system was developed, and three-dimensional discrete element analysis and soil bin tests were conducted. The results show that the masses of the convex and scale-like forms increased by 5.4% and 17%, respectively, and that the tangential cumulative forces decreased by about 40% and 70%, respectively. The wear mass decreased by 53% and 47%, respectively, compared with a prototypical wheel. The simulation shows that the durability increased significantly. The average tangential cumulative forces of the concave and ribbed shapes increased by more than 50%, and the wear mass decreased by 35% and 32%, respectively, compared with a prototypical wheel. The simulation shows that the results were not definitive. The analysis shows that the durability of the wheels can be improved via bionic optimization method. These results therefore provide a basis and reference for the design and optimization of the Mars rover's wheel surface. © Published under licence by IOP Publishing Ltd.

关键词： Wheels

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Positioning and Tracking of Neurons in Label-free Tissue Slice for Automatic Patch Clamping

Positioning and Tracking of Neurons in Label-free Tissue Sli...

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IEEE International Conference on robotics and Biomimetics

作者： Huiying Gong Jinyu Qiu Lu Li Yatong Yao Qili Zhao Xin Zhao Mingzhu Sun Institute of Robotics and Automatic Information System (IRAIS) and the Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

ISBN: (纸本)9781665405362

Neuron positioning is one crucial step of image-guided patch clamp, which is a "gold standard" approach to the study of ion channel biophysics and pharmacology at the molecular level directly. In this paper, we proposed a positioning and tracking method of neurons in label-free tissue slice. Neuron selection, positioning, and segmentation were achieved by designing a two-step positioning algorithm based on convolutional neural networks. Then the contour obtained was used to track the target neuron consistently and accurately, since the neuron will shift as the pipette approaching. In experiments, the proposed method reached 81.4% F1-score (precision = 82.8%, recall = 80%) in neuron positioning, and achieved a success rate of 97.5% in neuron 2D tracking. This method can be applied to automatic image-guided patch clamp systems in the future.

关键词： Training Image segmentation Target tracking Three-dimensional displays Neurons Ions Clamps

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Zebrafishtracker: A multi-zebrafish tracking algorithm can effectively solve cross occlusion

Zebrafishtracker: A multi-zebrafish tracking algorithm can e...

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IEEE International Conference on robotics and Biomimetics

作者： Zhenhua Fu Yiwen Wang Xin Zhao Mingzhu Sun Institute of Robotics and Automatic Information System (IRAIS) and the Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

ISBN: (纸本)9781665405362

Zebrafish is a model organism, which is widely used in life science and medicine research due to its high homology with human genes. How to handle cross-cases and achieve more comprehensive tracking is always a challenge. Zebrafishtracker proposed in this paper uses the instance segmentation and the skeleton stability analysis strategy to effectively solve the problem of detection error caused by the frequent crossover of multiple zebrafish. Then 2D tracking of zebrafish is realized based on identity information. The results show that in two relatively complex videos, MOTA of our algorithm in the top-view reaches more than 95%.

关键词： Performance evaluation Three-dimensional displays Conferences Fish Skeleton Stability analysis Life sciences

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Coordinate Descent Clustering with Trace Difference Criterion for Joint Clustering and Feature Extraction

SSRN

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SSRN 2023年

作者： Wang, Quan Wang, Fei Li, Zhongheng Wang, Zheng Nie, Feiping Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing100094 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Northwestern Polytechnical University Shaanxi Xi’an710072 China

Joint clustering and dimensionality reduction methods are a promising solution to clustering due to its scalability to high-dimensional data. Some methods leverage trace ratio criterion and attain clusters by borrowing the K-means algorithm. However, trace ratio criterion has no close-formed solution for the discriminative projection matrix and the K-means algorithm has a limited capacity to handle the many-cluster problem. In this paper, Coordinate Descent Clustering with Trace Difference criterion (CDCTD) is proposed for joint clustering and feature extraction. Formulating the objective function as a direct trace difference criterion containing a balance parameter, CDCTD harmonizes between-cluster scatter maximization and within-cluster scatter minimization by the balance parameter. Using the direct trace difference criterion, CDCTD can straightforward solve for the discriminative projection matrix and avoid obtaining a poor discriminative projection matrix in the iterative manner when a bad cluster start is given. CDCTD uses the coordinate descent method for clustering, improving the ability to address the many-cluster problem. Extensive experiments show that CDCTD has achieved significant performance improvements compared to previous trace ratio criterion related joint clustering and feature extraction methods, and also outperformed other clustering methods in most cases. © 2023, The Authors. All rights reserved.

关键词： Feature extraction

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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A kind of biomimetic control method to anthropomorphize a redundant manipulator for complex tasks

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Science China(Technological Sciences) 2020年第1期63卷 14-24页

作者： MO Yang JIANG ZhiHong LI Hui YANG Hong HUANG Qiang School of Mechatronic Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing 100081China Key Laboratory of Biomimetic Robots and Systems Ministry of EducationBeijing 100081China Institute of Manned Spacecraft System Engineering China Academy of Space TechnologyBeijing 100080China

It is an urgent problem for robots to operate complex tasks with some unknown motion mechanisms caused by the strong coupling of force and motion. However, humans can perform complex tasks well due to their natural evolution and postnatal training. A novel biomimetic control method based on a human motion mechanism with high movement adaptability is proposed in this paper. The core is to present a novel variable-parameter compliance controller based on human operation mechanisms with an action-planning method derived from optimization by human motion, and the main contribution is to change the parameters of compliance controller according to human operating intention synchronized with humanoid motion;this change could establish a humanoid map between the force and motion for a seven degree-of-freedom redundant manipulator to deal with the unknown motion mechanism in complex tasks, so the redundant manipulator can operate complex tasks with high performance. Sufficient experiments were performed, and the results validated the effectiveness of the proposed algorithm.

关键词： redundant manipulator biomimetic control humanoid mapping complex task

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Semantic Geometric Fusion Multi-object Tracking and Lidar Odometry in Dynamic Environment

arXiv

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arXiv 2022年

作者： Ma, Tingchen Ou, Yongsheng The Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China The Key Laboratory of Human-Machine-Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

The SLAM system based on static scene assumption will introduce huge estimation errors when moving objects appear in the field of view. This paper proposes a novel multi-object dynamic lidar odometry (MLO) based on semantic object detection technology to solve this problem. The MLO system can provide reliable localization of robot and semantic objects and build long-term static maps in complex dynamic scenes. For ego-motion estimation, we use the environment features that take semantic and geometric consistency constraints into account in the extraction process. The filtering features are robust to semantic movable and unknown dynamic objects. At the same time, a least square estimator using the semantic bounding box and object point cloud is proposed to achieve accurate and stable multi-object tracking between frames. In the mapping module, we further realize dynamic semantic object detection based on the absolute trajectory tracking list (ATTL). Then, static semantic objects and environmental features can be used to eliminate accumulated localization errors and build pure static maps. Experiments on public KITTI data sets show that the proposed system can achieve more accurate and robust tracking of the object and better real-time localization accuracy in complex scenes compared with existing technologies. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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