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Chinese Control and Decision Conference, CCDC

作者： Sichao Zhang Wei Liang Xudong Yuan Haibo An Meng Zheng Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Science and Technology on Information Systems Engineering Laboratory the 28th Research Institute of CETC Nanjing China

Automatic Guided Vehicle (AGV) has been widely used in the warehouse for transporting the bulky and heavy cargos. However, the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sent form the server due to, e.g., cyber attacks, unexpected blocks of the wireless signals. In order to ensure AGV running safely, this paper presents a visual surveillance system by making full use of the measurements from the forward and downward cameras. Specifically, the forward camera estimates the AGV positions and attitudes by tracking the surrounding landmarks detected from the forward image sequences. Besides, the downward camera is used to detect the QR codes fixed on the floor and estimate the AGV poses in the absolute reference frame. Apart from that, the AGV poses from the downward camera could correct scale and poses estimated the forward view. The proposed method has been extensively performed on the developed platform. The results proves the effectiveness in using the complementary forward-downward visual measurements for AGV security surveillance.

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Koopman Representation for Boolean Networks

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IFAC-PapersOnLine 2023年第2期56卷 6678-6683页

作者： Hongsheng Qi Maria Elena Valcher Guodong Shi Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China Dipartimento di Ingegneria dell'Informazione Universita’ di Padova Padova 35131 Italy Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW 2006 Australia

Boolean networks, as logical dynamical systems whose system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. The representation and control of Boolean networks have attracted a lot of attention in recent years. On a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems in early 1930s, which shows that using observable functions all nonlinear dynamics can be represented as (infinite dimensional) linear systems. In this paper, we present a framework for representing Boolean networks via Koopman approach. First of all, we construct addition and scalar multiplication operations over the set of logical functions over the binary field, defining a linear Boolean function space. Then associated with any Boolean mapping, the induced Koopman operator is defined as an operator over such Boolean function space. Next, we show that if there exists a set of logical functions that are invariant in the Koopman sense, a Boolean network can be represented by a finite-dimensional linear system. This Koopman perspective for Boolean networks is also extended to controlled Boolean networks.

关键词： Boolean networks Koopman operator

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Collision-free Navigation of Magnetic Mobile Microrobot in Multiple Scenarios

Collision-free Navigation of Magnetic Mobile Microrobot in M...

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IEEE International Conference on robotics and Biomimetics

作者： Yueying Tang Yi Xing You Li Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9781665481106

Microrobot has been developed for the manipulation of micro- and nanoscale objects for many biological and manufacturing tasks. However, there are still challenges in the collision-free operation of microrobots in multiple scenarios. Essential functions, such as path planning and autonomous and adaptive navigation in dynamic environments, are urgently needed to implement microrobots in practical scenarios. Here, we implement path planning and the autonomous navigation of microrobots in 2D static obstacle scenarios and micro-mazes. A probabilistic-based RRT algorithm is employed to speed up the path search in static obstacle scenarios. The Dijkstra algorithm is employed in the micro-maze navigation of the microrobot to avoid the narrow and long pipeline effect. To further ease the active manipulation of magnetic mobile microrobots, a handle-based interactive operation is developed to realize the operational tasks in the three-dimensional space based on artificial vision planning and navigation, which improves the interactivity and flexibility of the system, and supplements the current limitation of autonomous navigation on the three-dimensional space.

关键词： Visualization Navigation Magnetic resonance imaging Heuristic algorithms Probabilistic logic Path planning Real-time systems

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Semantic Mapping Based on Visual SLAM with Object Model Replacement Visualization for Cleaning Robot

Semantic Mapping Based on Visual SLAM with Object Model Repl...

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IEEE International Conference on robotics and Biomimetics

作者： Zirui Wang Haiou Liao Zhenzhong Jia Jing Wu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems they are also with Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

ISBN: (纸本)9781665481106

Cleaning robots have been widely used in our daily life, achieving huge success in the service robot sector. The autonomous movement and decision-making of these robots directly depend on their environmental perception capability, which is implemented using SLAM (simultaneous localization and mapping) technique. In order to achieve better environmental perception and intelligent decision-making, it is necessary to introduce visual SLAM into cleaning robot and take full advantage of visual information to achieve higher-level perception, instead of sticking to current feature point or pixel level perception capability. In this paper, we propose a framework for semantic mapping with object model replacement visualization in indoor scenes for cleaning robot. We use an EKF-based method to fuse wheel odometry and visual odometry, and build a map representation for navigation in the framework. We obtain a semantic map by fusing object detection and point cloud segmentation. We also develop object model replacement for better visualization purposes. Finally, we conduct dataset tests and real experiments to validate our proposed framework.

关键词： Visualization Simultaneous localization and mapping Service robots Biological system modeling Semantics Decision making Wheels

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Development of Autonomous Underwater Robot for Navigation through Narrow Passages

Development of Autonomous Underwater Robot for Navigation th...

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IEEE International Conference on robotics and Biomimetics

作者： Yang Luo Xiyu Zhu Yuchuan Zhou You Li Zhihui Xu Yan Wei Wende Ke Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9781665481106

Autonomous Underwater Vehicle (AUV), also called autonomous underwater robot, refers to an underwater robot that can independently complete tasks such as autonomous navigation, autonomous obstacle avoidance, and autonomous operation without human intervention. In some complex and narrow detection scenarios, autonomous underwater robots need to have a small volume, a high level of autonomy, and good maneuverability. Here, we design a miniature autonomous underwater robot driven by propellers, which integrates a high-performance processor, camera module, high-precision inertial measurement unit (IMU), etc. The attitude and position information of the robot is obtained in real-time through the IMU, and the processor controls the motion state of the six propellers, achieving the motion in six degrees of freedom in space. The highly integrated design ensures the maximum length of the whole machine within 15 cm, the 3-way PID controller design ensures an efficient and stable attitude control, and the high-performance processor provides more possibilities for target tracking and recognition. The developed AUV in this study shows superior navigation performance through narrow passages.

关键词： Autonomous underwater vehicles Propellers Attitude control Dynamics Process control Propulsion Aerospace electronics

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A new structure of end-effector traction upper limb rehabilitation robot

A new structure of end-effector traction upper limb rehabili...

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

作者： Li, Liaoyuan Han, Jianhai Li, Xiangpan Guo, Bingjing Xia, Pengpeng Du, Ganqin Henan University of Science and Technology Key Laboratory of Robotics and Intelligent Systems School of Mechanical and Electrical Engineering Luoyang471000 China First Affiliated Hospital of Henan University of Science and Technology Department of Neurology Luoyang471000 China

ISBN: (纸本)9781665436786

Among the rehabilitation therapies for patients with stroke or paralysis, robot-assisted rehabilitation is a research hotspot now. However, there are not many cases of clinical application, mainly because of the complex structure, single function, or high cost. This research proposes a new type of 3-DOF (degrees of freedom) upper limb rehabilitation robot in series structure of with an end-effector, which has 2 degrees of freedom in horizontal rotation and 1 degree of freedom in the vertical movement. It has a compact structure, saves space, is easy to be moved and can realize rehabilitation training in three-dimensional space. It is mainly used for rehabilitation training of the shoulder and elbow joints of the upper limbs. The first two rotary joints are driven by AC servo motors, and the prismatic joint is driven by a single-acting cylinder, which increases the passive compliance of the robot. In addition, a three-dimensional force sensor is added to expand the human-machine interaction channel and increase the active safety of the robot. Through the trajectory tracking and force control test of the robot, it is proved that the device can meet the demand of passive and active upper limb rehabilitation. © 2021 IEEE.

关键词： End effectors

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Nonvolatile and SEU-Recoverable Latch Based on FeFET and CMOS for Energy-Harvesting Devices

Nonvolatile and SEU-Recoverable Latch Based on FeFET and CMO...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Aibin Yan Zhuoyuan Lin Guangzhu Liu Qingyang Zhang Zhengfeng Huang Jie Cui Xiaoqing Wen Patrick Girard School of Computer Science and Technology Anhui University Hefei China School of Microelectronics Hefei University of Technology Hefei China Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Laboratory of Informatics Robotics and Microelectronics of Montpellier University of Montpellier / CNRS Montpellier France

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Nonvolatile memories are widely used in emerging energy-harvesting Internet-of-Things (IoT) applications, and nonvolatile memories constructed from FeFET devices hold great promise. This paper presents a nonvolatile and single-event-upset (SEU)-recoverable latch based on FeFET and CMOS for energyharvesting devices. The latch uses n-type FeFET devices to provide nonvolatility without any additional control signals. Moreover, since the soft error problem has become increasingly severe, radiation hardening by design gains a great attention as a promising approach to mitigate the reliability issue. The latch uses feedback interlocked loops with n-type FeFETs and C-elements, enabling it to provide nonvolatility and SEU-recovery simultaneously. Simulation results with Candence Virtuoso verifies that the proposed latch design has correct functioning with excellent performance compared to the state-of-the-art designs.

关键词： Performance evaluation Latches Nonvolatile memory Radiation hardening (electronics) Circuits and systems Simulation Reliability engineering

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Research on Multiple Automated Guided Vehicles Path Planning to Reduce Default Time 2

Research on Multiple Automated Guided Vehicles Path Planning...

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2nd IEEE International Conference on Data science and Computer Application, ICDSCA 2022

作者： Liu, Yiyang Yan, Shuaihua Hou, Zheng Zhao, Yang Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China Kunshan Intelligent Equipment Research Institute Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China University of Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China College of Information Science and Engineering Northeastern University Shenyang China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

This paper studies the path planning problem of multiple automated guided vehicles (multi-AGV) in a matrix manufacturing workshop. We proposed the multi-AGV path planning problem with default time, which is a variant of the classic path planning problem. In order to ensure the timely completion of each task, the default time of the task is explicitly considered. The goal is to obtain a conflict-free path with the minimum total default time, total time, and total path length. For these three goals, this problem is NP-hard. In order to solve this problem better, we established a multi-objective optimization model of total default time, total time and total path length of multi-AGV in flexible manufacturing environment. This paper proposes a multi-AGV path planning method that integrates game theory and A∗ algorithm. This method regards each AGV as a participant in the game model, through the default time obtained from each game dynamically adjusts the probability of each AGV planning the next path, and uses game theory to help the system dynamically select the most suitable AGV to plan the next path to improve the on-time delivery rate of tasks. Finally, the simulation results show that the multi-AGV path planning method integrating game theory and A∗ algorithm further reduces the total default time, total time and total path length of all AGVs. © 2022 IEEE.

关键词： Motion planning

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Edge Detectors Can Make Deep Convolutional Neural Networks More Robust

arXiv

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arXiv 2024年

作者： Ding, Jin Zhao, Jie-Chao Sun, Yong-Zhi Tan, Ping Wang, Jia-Wei Ma, Ji-En Fang, You-Tong School of Automation and Electrical Engineering Key Institute of Robotics of Zhejiang Province Zhejiang University of Science and Technology Hangzhou310023 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China School of Electrical Engineering Zhejiang University Hangzhou310027 China

Deep convolutional neural networks (DCNN for short) are vulnerable to examples with small perturbations. Improving DCNN’s robustness is of great significance to the safety-critical applications, such as autonomous driving and industry automation. Inspired by the principal way that human eyes recognize objects, i.e., largely relying on the shape features, this paper first employs the edge detectors as layer kernels and designs a binary edge feature branch (BEFB for short) to learn the binary edge features, which can be easily integrated into any popular backbone. The four edge detectors can learn the horizontal, vertical, positive diagonal, and negative diagonal edge features, respectively, and the branch is stacked by multiple Sobel layers (using edge detectors as kernels) and one threshold layer. The binary edge features learned by the branch, concatenated with the texture features learned by the backbone, are fed into the fully connected layers for classification. We integrate the proposed branch into VGG16 and ResNet34, respectively, and conduct experiments on multiple datasets. Experimental results demonstrate the BEFB is lightweight and has no side effects on training. And the accuracy of the BEFB integrated models is better than the original ones on all datasets when facing FGSM, PGD, and C&W attacks. Besides, BEFB integrated models equipped with the robustness enhancing techniques can achieve better classification accuracy compared to the original models. The work in this paper for the first time shows it is feasible to enhance the robustness of DCNNs through combining both shape-like features and texture features. © 2024, CC BY-NC-SA.

关键词： Convolutional neural networks

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Organic Heterojunction Enabled Near 1% H2o2 Photoproduction with Ultrafast Charge Separation

SSRN

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SSRN 2024年

作者： Liu, Jingjing Hu, Qiushi Liu, Shang Lin, Meng Zhang, Xiaosa Xie, Ying Chen, Xihan Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems SUSTech Energy Institute for Carbon Neutrality Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Key Laboratory for Rare Earth Chemistry and Application of Liaoning Province College of Science Shenyang University of Chemical Technology Liaoning Shenyang China

Hydrogen peroxide (H2O2) finds wide application in disinfection, chemical production, and bleaching owing to its sustainability, stability, and ease of storage compared to hydrogen. However, the current industrial engineering practices for producing photocatalysts used in H2O2 generation face challenges such as low yields with organic catalysts and high costs associated with inorganic catalysts. In light of these challenges, we investigate a viable method utilizing a simple condensation reflux technique to synthesize pure organic heterojunction photocatalysts featuring a π-π stacked structure derived from graphitized carbon nitride (melem) and meso-tetrakis (4-carboxyphenyl) porphyrin. This approach enables efficient H2O2 production from water, seawater, and oxygen without the necessity of sacrificial agents. In this study, the synthesized catalyst demonstrates an impressive H2O2 production rate of 106 mmol/h.g.L under seawater conditions and 77.67 mmol/h.g.L under pure water conditions in ambient air. Following a reaction time of 4.5 hours, the H2O2 concentration reaches 0.88 wt% with a volume of 5.0 mL. Transient absorption spectroscopy validates the formation of a heterojunction between melem and porphyrin. Notably, this heterogeneous catalyst efficiently facilitates water oxidation and oxygen reduction while suppressing both H2O2 decomposition and subsequent photodecomposition reactions, thereby addressing the challenges associated with organic catalyst yield. © 2024, The Authors. All rights reserved.

关键词： Absorption spectroscopy

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