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

作者： Pan, Cunyi Wang, Ting Liu, Zide Shao, Shiliang Quan, Zhifan Shenyang Li Gong University Shenyang110000 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350315196

The balancing robot's design principle and implementation method are based on the second-order complementary filtering algorithm, which includes establishing the hardware platform, writing the software program, and analyzing the experimental test results. Based on the STM32407 microcontroller chip, a design scheme of a two-wheeled self-balancing robot system is presented. The system scheme includes STM32407 microcontroller circuit design, vehicle attitude sensor BMI088 detection circuit design, motor drive circuit design, and PID controller as the core software design through the DR16 module to communicate with the mobile terminal. In terms of software, the PID control method based on the second-order complementary filtering algorithm is adopted to realize the control and movement of the balanced robot through real-time control of motor output and steering. In terms of experimental testing, the balancing and moving abilities of the balancing robot were tested by placing the balancing robot on a plane and a sloped surface. The experimental results show that the balanced vehicle design based on the second-order complementary filtering algorithm has better balance control and motion control capabilities and can achieve balance and movement on different slope surfaces. © 2023 IEEE.

关键词： Real time control

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Dexterity of Concentric Magnetic Continuum Robot with Multiple Stiffness 16th

Dexterity of Concentric Magnetic Continuum Robot with Multip...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Li, Na Lin, Daojing Wu, Junfeng Gan, Quan Jiao, Niandong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819965007

With the advancement of minimally invasive surgery, research pertaining to miniature continuum robots is progressively gaining momentum. In contrast to non-magnetic continuum robots, magnetic continuum robots (MCRs) exhibit a simple structure and dexterous operation characteristics, as they can be remotely and wirelessly controlled through magnetic manipulation. Dexterity serves as a vital parameter in evaluating MCRs. Nevertheless, conventional MCRs encounter limited dexterity and controllability issues due to their soft bodies. To enhance the dexterity of MCRs, we propose a novel concentric magnetic continuum robot (C-MCR), comprising a magnetic catheter and magnetic guidewire in a concentric combination. The substantial discrepancy in stiffness between the catheter and the guidewire facilitates the C-MCR to operate in four working modes, resulting in superior dexterity. Within this study, we evaluated the dexterity of the C-MCR utilizing a homemade eight-coil electromagnetic system. The experimental findings demonstrate that the C-MCR exhibits better dexterity, simplified operation, minimal risk, and promising prospects for clinical applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Catheters

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Cooperative attack–defense decision-making of multi-UAV using satisficing decision-enhanced wolf pack search algorithm

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Soft Computing 2024年第17-18期28卷 9575-9586页

作者： Zhou, Tongle Chen, Mou Wang, Yuhui Zhu, Ronggang Yang, Chenguang College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Avionics System Integrated Technology Shanghai200241 China Science and Technology on Electro-optic Control Laboratory Luoyang Institute of Electro-Optical Equipment of Avic Luoyang471000 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

Unmanned aerial vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack–defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack–defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. To improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Decision making

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Curing curve prediction using genetic algorithm optimized back propagation neural network 9

Curing curve prediction using genetic algorithm optimized ba...

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2023 9th International Forum on Manufacturing Technology and Engineering Materials, ICMTEM 2023

作者： Zhang, Ruming Guan, Kunpeng Wu, Chenchen Shenyang University of Technology Shenyang110870 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Science and Technology Liaoning Anshan114051 China

Thermoset composites constructed with monolithic moulding can significantly reduce the number of parts and connectors, improve the reliability of the composite structure, and reduce production costs. For such composite components, the degree-of-cure (DoC) curve is normally considered to evaluate the curing process, so that the curing process-induced deformation and residual stress can meet the manufacturing requirements. In this paper, a method is proposed to predict the DoC curve based on the neural network. First, the DoC curves for AS4/3501-6 composite structures were obtained from ABAQUS and HETVAL subroutine, and the results were verified by published values. Next, the curves of temperature over time and DoC over time were generated to train the neural network. Finally, the back propagation (BP) neural network is optimized using the genetic algorithm (GA), and the DoC curve prediction model is created. The results demonstrate that, with a maximum error of 3.24%, the simulated curves essentially correspond with published values. Evaluation and validation analyses show that the prediction of the DoC curve using the GA-BP neural network yields high computational efficiency and accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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RDDS: Road Disease Detection Model Based on YOLOv5 14

RDDS: Road Disease Detection Model Based on YOLOv5

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14th IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent systems, CYBER 2024

作者： Han, Zhiqiang Gong, Jun Qiao, Yu School of Vehicle and Transportation Engineering Taiyuan University of Science and Technology Taiyuan030024 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China

ISBN: (纸本)9798331506056

The utilization of intelligent vehicles for detecting road anomalies has become a relatively common phenomenon. The existing road disease detection workload is large, the robustness is not high, and small diseases are easily ignored, which brings huge challenges to road disease detection. A road disease detection model named RDDS based on YOLOv5 is proposed. Based on the YOLOv5 algorithm, we incorporate Transformer encoder blocks into the head part to form Transformer Prediction Heads (TFE), expanding their number to four. This enhancement aims to improve the model's capability to detect small targets and road diseases of different scales. In addition, we introduce the convolutional block attention model (CBAM) to make the network pay more attention to important channels and spatial locations, thereby improving the performance and generalization ability of the model. Aiming at the problems of low resolution and insufficient data volume in current road disease data sets, we propose a new road disease detection data set RDDSC. Finally, we conducted experiments on the RDDSC data set. The experimental results showed that compared with the original YOLOv5, the RDDS parameters increased slightly, while the detection accuracy was significantly improved. Compared with existing detection algorithms, RDDS has obvious advantages in road disease detection. © 2024 IEEE.

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Optimization of a Piezoelectric Bending Beam-based Human Knee Energy Harvester 20

Optimization of a Piezoelectric Bending Beam-based Human Kne...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Liao, Haisu Wang, Yidi Shi, Qiuyu Huang, Ruisen Gao, Fei Guangdong Provincial Key Lab 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 System

ISBN: (纸本)9798350320831

The concept of extracting energy from the human body to recharge depleted energy sources has gained significant attention. Recently, scientists have focused on harnessing biomechanical energy from the human body while walking. The aim of this study is to optimize a piezoelectric bending beam-based human knee energy harvester to enhance performance. Specifically, the shape of the bending beam (the substrate: a carbon fiber plate) is optimized to modulate the deformation, such that the average strain of the piezoelectric macro fiber composites (MFC) attached to the bending beam is improved to generate more electricity. In addition, the effects of the substrate's thickness and the hinge base's height for the bending beam on the output power are also analyzed. Experimental testing on a subject is conducted to validate our design and test the performance. The harvester generates an average power output of 24.55 mW when walking at 4 km/h on a treadmill. The harvester's total weight is 278g. © 2023 IEEE.

关键词： Energy harvesting

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A Lightweight YOLOv5 Model Integrating GhostNet and Attention Mechanism 4

A Lightweight YOLOv5 Model Integrating GhostNet and Attentio...

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4th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2023

作者： Dou, Xinke Wang, Ting Shao, Shiliang School of Information Engineering Shenyang University of Chemical Technology Shenyang China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350326444

Aiming at the problems of complex structure of neural network, large number of parameters and difficult deployment to terminal devices, this paper proposes an improved lightweight object detection model for the purpose of building a model with high classification accuracy and low complexity. First, the one-stage detector yolov5 is used as the base network. Considering the excessive redundant features of feature extraction, Ghost module is used to replace the traditional convolution, effectively allocate computing resources, to reduce the size of the model and improve the speed of model detection. When designing model bottleneck structure, Normalization-based Attention Module (NAM) is added to improve training efficiency and reduce model complexity. Experimental results show that compared with YOLOv5, the calculation speed of the proposed model is increased by 17% and the accuracy is reduced by less than 2%, which is of great significance in the environment of low-performance computing equipment. © 2023 IEEE.

关键词： Object detection

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Efficient and Hierarchical Quadrotor Planner for Fast Autonomous Flight 16th

Efficient and Hierarchical Quadrotor Planner for Fast Auto...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Nie, Hongyu Chen, Jiantan Zhang, Guangyu Li, Decai He, Yuqing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819965007

In this paper, we propose an effective and hierarchical planning framework for quadrotor fast autonomous flight. In the front-end, we propose an efficient guided sampling strategy by topology graph. In the back-end, the traditional trajectory optimization problems are formulated as minimising an objective function such as total energy cost while considering safety and dynamic feasibility constraints. However, the time characteristic is ignored. In this paper, the time optimal trajectory is studied, the time optimal trajectory problem is transformed to a convex optimization problem with a time optimal guidance trajectory based on the Pontryagin’s Minimum Principle. The simulation experimental results demonstrate the feasibility and validity of the proposed motion planning method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Topology

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Self-Organized Circling of Swarm Robots using Optical Communications 13

Self-Organized Circling of Swarm Robots using Optical Commun...

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

作者： Qin, Xiaoyang Yang, Yongliang Pan, Mengyun Liu, Lianqing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China The University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350315196

Morphogenetic engineering aims to develop self-organized methods to form the predesigned morphology of robot swarms. A simple method has been reported to form the circling morphology of fish robot swarms in experiments and of ground robot swarms in simulations. This method requires limited hardware of robots and minimum on-board communication, which makes it easy to scale up. The robot swarm on the ground, however, is significantly different from that underwater. Using our homemade Morphobot platform, we adapted this method to generate the circling morphology of a swarm of robots on the ground. For this application, we customized Morphobots with optical sensors and light emission devices. We first demonstrated the effectiveness of this adapted method. In self-organized systems, the relationship between the global pattern and the properties of individual robots is implicit. It is thus still challenging to design a controller for this type of dynamic system. To clarify this relationship in this circling morphogenesis, we evaluated the effects of two important features of robots on the formation of the circling pattern. We Second experimentally evaluated the effects of the moving radius and ranges of light emission of individual robots on the circling morphology. These results shine light on developing a reliable and rigid engineering methodology for swarm robotics. © 2023 IEEE.

关键词： Morphology

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Disturbance Observation and Control of Operational Unmanned Aerial Vehicles

Disturbance Observation and Control of Operational Unmanned ...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Yao, Guanyu Yang, Liying Chang, Yanchun He, Yuqing School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350316308

UAVs are used widely in all works and life, and their operation forms and application scenarios are more complex than ever before. In order to deal with various disturbances faced by operational UAVs in application scenarios and achieve stable control, a disturbance observation and compensation structure combining linear extended state observer and sliding mode controller is proposed to achieve stable control of operational UAVs. Firstly, the typical operational UAV is taken as the research object, and the kinematics and dynamics models are established. Then, a linear extended state observer is designed to estimate the environment and body disturbances, and the sliding mode control method is combined to control the system. Finally, the effectiveness of the designed control method is verified through simulation. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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