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42nd Chinese Control Conference, CCC 2023

作者： Zeng, Ming Li, Siying Liu, Jiazhe Li, Yuanhao Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China

ISBN: (纸本)9789887581543

The ability of continuously learning new knowledge without forgetting old ones is crucial to adapt to an ever-changing world. This scenario becomes more challenging when the previous data are not available. Current class incremental learning (CIL) approaches tend to incorporate new classes with backward compatibility, i.e., maintaining discriminability of old ones. By contrast, we focus on the extensibility and compatibility for future new classes in the early stage. Our proposed method achieves this by augmenting feature space. In detail, a large number of pseudo-new classes are generated via real example mixture and then train the initial spatially augmented model using pseudo-new classes and the base classes. Besides, considering the fact that it is impossible to maintain backward compatibility with only one prototype for each old class, the updated model also needs to preserve old class space in incremental stages. We employ a certain perturbation to the old class prototypes to effectively avoid old class space from being over-squeezed by the samples of new classes. The experiments on CIFAR-100 and ImageNet-Subset (100 classes) demonstrate that our method substantially reduces the overlap of old and new classes, outperforming state-of-the-art various baselines. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Catastrophic forgetting Class incremental learning Feature space augmentation Old class space preservation Pseudo-new classes

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Application Research of Landmarks in Path Planning Algorithms of Mobile Robots 2

Application Research of Landmarks in Path Planning Algorithm...

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2nd International Conference on Digital Society and Intelligent systems, DSInS 2022

作者： Fan, Linghao Liu, Xiangde Zhang, Yi Chongqing University of Posts and Telecommunications Intelligent Systems and Robotics Laboratory Chongqing China Chongqing Information Accessibility and Service Robot Engineering Technology Research Center Chongqing China

ISBN: (纸本)9781510663244

A way of incorporating landmark information matrix QR to affect the global path planning algorithm is proposed for the use of landmarks in robot localization and navigation. It is also investigated how this method affects the pace at which the original algorithm solves problems. The reward and punishment items in this technique include dangerous locations with lots of obstacles around them, landmarks with location information connected to the ground, and the two combined. Three representative common robot path planning algorithms are also imposed as influences. Through MATLAB simulation experiment, find the optimal path planning algorithm that is appropriate for applying reward and punishment by comparing the quality of the robot's driving path and the algorithm solution speed before and after the reward and punishment. According to the simulation results, the reward and punishment approach is practical and efficient. The heuristic search algorithm is better suited for reward and punishment, and both its path quality and speed of solution have greatly increased. © 2023 SPIE.

关键词： Genetic algorithms

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Trajectory Control of Multi-Axis Robotic Arms Based on Physics-Informed Neural Networks and Nonlinear Model Predictive Control

Trajectory Control of Multi-Axis Robotic Arms Based on Physi...

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2024 China Automation Congress, CAC 2024

作者： Wang, Yiqing Xia, Changqing Jin, Xi Xu, Chi Zhang, Yanzhu School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China 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

ISBN: (纸本)9798350368604

Multi-axis robotic arms are extensively utilized in intelligent manufacturing scenarios, with trajectory control in flexible scenarios constituting a primary challenge. Physics-Informed Neural Networks (PINNs) represent advanced methods that integrate physical laws with data-driven approaches. Despite their outstanding performance in integrating theory and data, research on their application for controlling robotic arms in complex scenarios remains limited. This paper establishes a nonlinear dynamic model based on the physical relationships between the axes of robotic arms. In the absence of prior data, Sobol sequence random sampling is employed to generate data, which are subsequently trained using PINNs. Considering system noise, the Extended Kalman Filter (EKF) is utilized to predict the next state in noisy environments, and Nonlinear Model Predictive Control (NMPC) is implemented to control the robotic arm for trajectory tracking, achieving real-time control. Simulation results demonstrate that the proposed Discrete Physics-Informed Predictive Control (DPIPC) method exhibits smaller position and velocity errors with less fluctuation compared to the method in the reference, indicating superior control capabilities. © 2024 IEEE.

关键词： Extended Kalman filters

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A Novel Fish-inspired Self-adaptive Approach to Collective Escape of Swarm Robots Based on Neurodynamic Models

A Novel Fish-inspired Self-adaptive Approach to Collective E...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Junfei Li Simon X. Yang Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph Guelph Canada

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Fish schools present high-efficiency group behaviors to collective migration and dynamic escape from the predator through simple individual interactions. The purpose of this research is to infuse swarm robots with "fish-like" intelligence that will enable safe navigation and efficient cooperation, and successful completion of escape tasks in changing environments. In this paper, a novel fish-inspired self-adaptive approach is proposed for the collective escape of swarm robots. A bio-inspired neural network (BINN) is introduced to generate collision-free escape trajectories through the dynamics of neural activity and the combination of attractive and repulsive forces. In addition, a neurodynamics-based self-adaptive mechanism is proposed to improve the self-adaptive performance of the swarm robots in dynamic environments. Similar to fish escape maneuvers, simulations and real-robot experiments show that the swarm robots can collectively leave away from the threat and respond to sudden environmental changes. Several comparison studies demonstrated that the proposed approach can significantly improve the effectiveness, efficiency, and flexibility of swarm robots in complex environments.

关键词： Uncertainty Navigation Biological system modeling Dynamics Neural activity Swarm robotics Trajectory

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Acceleration-level coordinated control of a dual-arm free-floating space robot under hard joint constraints

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Advances in Space Research 2025年第11期75卷 8122-8139页

作者： Xue, Zhihui Liu, Jinguo Zhang, Xin Zhou, Hao Li, Yangmin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Kowloon999077 Hong Kong School of Electrical and Mechanical Engineering University of Portsmouth PortsmouthPO1 3DJ United Kingdom

Dual-arm space robots are becoming increasingly crucial in on-orbit servicing missions. The online motion control of a dual-arm redundant space robot with hard joint constraints presents significant challenges due to its free-floating base. In this article, we proposed an acceleration-level coordinated control framework to solve hard joint constraints and dynamic singularity. The proposed framework combines a task scheduling strategy to achieve saturation in the null space, so that different tasks can achieve trajectory tracking with minimal task scaling under given joint hard constraints. The framework can achieve efficient online control by sequentially abandoning the use of joints that exceed the joint constraint and reintroducing these commands at their saturation level by projecting them into the appropriate null space. Finally, we verify the tracking performance of the algorithm through numerical simulation and experimental research. By comparing the proposed algorithm with the quadratic programming and pseudo-inverse methods, the algorithm has shown excellent online motion control performance, with a computation time of approximately 1 ms within a single sampling period. © 2025 COSPAR

关键词： Quadratic programming

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Facial Emotion Recognition in Smart Education systems: A Review 9

Facial Emotion Recognition in Smart Education Systems: A Rev...

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9th IEEE International Smart Cities Conference, ISC2 2023

作者： Farman, Haleem Sedik, Admed Nasralla, Moustafa M. Esmail, Maged Abdullah College of Engineering Prince Sultan University Smart Systems Engineering Laboratory Department of Communications and Networks Engineering Riyadh Saudi Arabia Kafrelsheikh University Faculty of Artificial Intelligence Department of the Robotics and Intelligent Machines Kafrelsheikh Egypt

ISBN: (纸本)9798350397758

Facial Emotion Recognition (FER) plays a pivotal role in the realm of Smart Education systems (SES), catering to the growing need for personalized and adaptive learning experiences. This paper presents a comprehensive review of the current state-of-the-art techniques and methodologies employed in FER in general and within the context of SES in particular. The primary objective of this review is to explore the FER technology for the enhancement of educational environments. The review begins by providing an insightful overview of the significance of emotions in education, leveraging deep learning approaches to elucidate the impact of emotional states on cognitive performance and academic outcomes. Subsequently, it explores the key components and working principles of FER systems, encompassing the extraction, representation, and classification of facial emotions. Furthermore, this paper highlights the updated literature in the field of FER applied to SES, ranging from real-time emotion analysis during classroom interactions to adapting instructional content based on learners' emotional states. Furthermore, the review critically analyzes the existing facial emotion recognition datasets utilized in facial emotion recognition research. The dataset is subcategorized in to two parts, images and videos, providing readers with convenience in understanding the various data sources employed in FER model training and evaluation. © 2023 IEEE.

关键词： Face recognition

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A Battery Control Strategy for Sequential Utilization of Energy Storage systems in Power Batteries 7

A Battery Control Strategy for Sequential Utilization of Ene...

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7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Li, Bowen Cui, Shijie Zhu, Lizhong Shenyang Ligong University College of Automation and Electrical Engineering Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350339161

With the widespread adoption of energy storage systems utilizing power batteries, battery lifespan degradation has become a primary constraint on system performance. To address this issue, this study proposes a lifespan-optimized battery control strategy. Firstly, a battery lifespan calculation model for the energy storage system is established, taking into detailed consideration key parameters such as battery State of Charge (SOC). Secondly, a control strategy based on SOC for charging and discharging is designed, aiming to minimize battery lifespan consumption to the greatest extent possible. Finally, experimental results demonstrate that the proposed control strategy significantly improves the lifespan of the energy storage system compared to existing strategies. This research provides an effective means of control for the long-term stable operation of power battery systems. © 2024 IEEE.

关键词： Charging (batteries)

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Electrochemical Monitoring of Intracellular Reactive Oxygen Species Based on Automated Nanoprobe Platform

Electrochemical Monitoring of Intracellular Reactive Oxygen ...

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2023 Annual IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2023

作者： Ma, Yanmei Hu, Weikang Ruan, Muyang Zhan, Zhen Zhang, Yi Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen China City University of HongKong Department of Biomedical Engineering Hong Kong

ISBN: (纸本)9798350344486

The electrochemical detection of endogenous molecules from a single cell is a crucial technique for understanding fundamental cellular processes at the subcellular level and uncovering cellular heterogeneity. However, high throughput intracellular detection has posed significant challenges. This paper proposes a simple method for fabricating a nanoprobe for the electrochemical monitoring of intracellular reactive oxygen species (ROS), which are important signaling molecules that play a key role in a wide range of cellular processes, including apoptosis, proliferation, and differentiation. Combined with the automated nanoprobe platform, the study successfully achieved minimally invasive and efficient intracellular ROS detection in living cells. Moreover, the results reveal that the average ROS concentration in the cytoplasm and nucleus is uneven, which has important implications for the understanding of cellular redox signaling. © 2023 IEEE.

关键词： Nanoprobes

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STAPointGNN: Spatial-Temporal Attention Graph Neural Network for Gesture Recognition Using Millimeter-Wave Radar 19th

STAPointGNN: Spatial-Temporal Attention Graph Neural Network...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zhang, Jun Wang, Chunyu Wang, Shunli Zhang, Lihua Academy for Engineering and Technology Fudan University Shanghai China Jilin Provincial Key Laboratory of Intelligence Science and Engineering Changchun China Engineering Research Center of AI and Robotics Ministry of Education Shanghai China Engineering Research Center of AI and Unmanned Vehicle Systems of Jilin Province Changchun China

ISBN: (纸本)9783031545276

Gesture recognition plays a pivotal role in enabling natural and intuitive human-computer interaction (HCI), finding applications in diverse domains such as smart homes, robot control, and virtual reality. Thanks to advances in computer vision, the most popular method currently is to use the camera for gesture recognition. However, the camera struggles to function properly in poor lighting and inclement weather, and risks invading privacy. Due to the robust and non-invasive features of millimeter-wave radar, gesture recognition based on millimeter-wave radar has received extensive attention from researchers in recent years. In this paper, we propose a novel graph neural network named STAPointGNN for gesture recognition using millimeter-wave radar. In order to better extract features in the spatial and temporal dimensions of point clouds collected by millimeter-wave radar, we designed a spatial-temporal attention mechanism based on graph neural network. We also propose a novel point flow embedding method to capture the motion features of the point clouds in adjacent frames. To verify the superiority of our method, we conduct experiments on two public millimeter-wave radar gesture recognition datasets. The results show that our model outperforms existing mainstream algorithms. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Gesture recognition

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Development of a Vibration-driven Capsule Robot with Protruding Magnetic Bristles with Enhanced Adaptability in Wet and Dry Environments

Development of a Vibration-driven Capsule Robot with Protrud...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Zhang, Yujie Wei, Tanyong He, Shujing Hong, Yuying Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen518055 China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9798350325706

Colonoscopy is a widely used method for diagnosing bowel cancers, requiring coordinated efforts from medical professionals due to its invasive nature. In contrast, miniature capsule robots, measuring just a few centimeters, offer a less invasive diagnostic option by integrating multiple functions. However, current capsule robots face challenges with complex designs, limited mobility, size, and cost, which hinder their adoption and reduce gastrointestinal disorder screening rates. To address these issues, we introduce the vibration-driven capsule robot (VCR) with magnetic protruding bristle structures. Four simple components (shell structure, electronic components, permanent magnet, and magnetic soft bristles) are designed to improve the robot's mobility in dry and wet environments. The magnetic bristle structures are inspired by flexible organisms and enhance the robot's adaptability. The robot is propelled by centrifugal force from a vibration motor, allowing efficient movement along the intestinal tract while protecting the patient's lining. The fabrication process of the magnetic soft bristles has been refined to optimize material ratios and enhance the robot's performance. The vibration motor's output is analyzed using load cells to ensure efficiency. For precise path planning, an external permanent magnet (EPM) is applied to guide the capsule's direction. Experiments confirm the VCR's versatility, performing fluid linear and curved motions in different environments. These findings underscore the feasibility of the VCR as a potent tool for non-invasive, timely screening of gastrointestinal disorders. © 2023 IEEE.

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