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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Wang, Lei Hu, Yuxin Zhang, Zhaowei Jiang, Lin School of Mechanical and Automation Engineering Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781510667563

Proposed a method for calculating the area of road diseases using a monocular camera. The camera and the road plane are calibrated to obtain the mapping relationship between pixel points and spatial points;the Mask R-CNN is used to detect and segment the road disease;the inverse perspective transformation is used to convert the target image into a bird’s-eye view to obtain the relationship between the pixel scale and the real scale;binarize the bird’s-eye view according to the segmentation effect, and the area of the road disease could be obtained through calculating the number of target pixels. It has been verified that the calculation error of the algorithm is about 2.1675% in the near vicinity. © 2023 SPIE.

关键词： Birds

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Knowledge Graph-Based Product Sustainable Design for Low Carbon Footprint

Knowledge Graph-Based Product Sustainable Design for Low Car...

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International Conference on Mechanical Design, ICMD 2021

作者： Chen, Weihao He, Bin Yu, Qianyi Yuan, Xin Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9789811673801

The creation of domain knowledge graph plays a great role in promoting the development of the industry. The work done in this paper is a trial of the application of knowledge graph in the field of product low-carbon sustainable design. At the beginning of the article, the applicability and feasibility of knowledge graph in the field of product low-carbon sustainable design are analyzed. In the main part of article, the methods and technologies needed to construct knowledge graph in the field are summarized in a five-tier framework. Then methods based on knowledge graph to assist designers in creating life cycle models for product low-carbon sustainable design are introduced. Finally, through the overall analysis of the creation process of life cycle model under the effect of knowledge graph, a circular outward calculation method of node correlation which can adapt to a variety of scenarios is designed and applied. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Knowledge graph

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Workspace optimization of parallel robot by using multi-objective genetic algorithm

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High Technology Letters 2022年第4期28卷 411-417页

作者： WANG Jinhong LEI Jingtao School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444P.R.China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai 200444P.R.China

For the narrow workspace problem of the universal-prismatic-universal(UPU)parallel robotwith fixed orientation,a kind of multi-objective genetic algorithm is studied to optimize the robot’*** concept of the effective workspace and its solution method are *** effectiveworkspace height(EWH)and global condition number index(GCI)of Jacobi matrix are selected asthe optimized objective *** the robot in two different orientations,the geometric pa-rameters are optimized by the multi-objective genetic algorithm named non-dominated sorting geneticalgorithm II(NSGA-II),and a set of structural parameters is *** optimization results areverified by four indicators with the robot’s moving platform at different *** resultsshow that,after optimization,the fixed-orientation workspace volume,the effective workspace heightand the effective workspace volume increase by 32.4%,17.8%and 72.9%on average,*** decreases by 6.8%on average.

关键词： parallel robot multi-objective genetic algorithm workspace optimization

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AIRRT∗: An improved fast path planning algorithm for manipulators 3

AIRRT∗: An improved fast path planning algorithm for manipu...

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3rd International Conference on Advanced Materials and Intelligent Manufacturing, ICAMIM 2022

作者： Chen, Jie Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

Path planning algorithms based on sampling have been widely studied and applied in recent years, among which the Informed-RRT∗ algorithm is a typically progressive optimization algorithm. To overcome the weakness of low optimization efficiency of the Informed-RRT∗ algorithm, an improved algorithm AIRRT∗ (Adaptive Informed-RRT∗) is proposed, which can greatly improve optimization efficiency and improve the quality of optimized paths. According to the node distribution of the initial path, the appropriate node construction areas are dynamically selected first in the process of direct local sampling. Then collision detection and reconstruction are performed. Unlike the traditional algorithm, the AIRRT∗ algorithm determines the area to be reconstructed firstly, then performs direct local sampling in the reconstructed area, and finally reconstructs the path to improve the sampling efficiency. In addition, to reduce the searching difficulty of global path nodes, the invalid nodes are removed in reconstruction, which limits the growth of nodes in optimization. AIRRT∗ algorithm is compared with the common algorithms through simulation experiments, which proves that AIRRT∗ algorithm has obvious advantages in algorithm efficiency and path quality and has good applicability in varied scenarios. © Published under licence by IOP Publishing Ltd.

关键词： Motion planning

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Design and Development of a Visual - SLAM based Automated Guided Vehicle

Design and Development of a Visual - SLAM based Automated Gu...

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International Conference on Advances in Electronics, Computers and Communications (ICAECC)

作者： Ankur Bhargava Ajay S. Singholi Mohd. Suhaib Faculty of Engineering and Technology Jamia Millia Islamia Delhi India Robotics & Automation University School of Robotics & Automation India Delhi

ISBN: (数字)9798350305449

ISBN: (纸本)9798350305456

The automobile industry is currently undergoing fast change as big manufacturers devote their attention to the development of future self- driving vehicles or automated guided vehicles. As a result, mobile robots and current automotive technologies are integrating to create the area of autonomous navigation. The camera sensor is the one garnering the most attention in terms of autonomy sensor research due to the large amount of information it provides for object detection and classification algorithms in addition to depth, coloring, size, and texture recognition. In the last ten years, there have been significant advancements in computing capabilities and image analysis algorithms. The requirement for developing low-level motion controllers grew as a consequence of the increase in machine vision performance and capabilities. This article discusses mecanum wheel mobile robotic applications of vision and SLAM-based motion controller. When using sensors like cameras or Lidar, autonomous mobile robots usually use the vision- based & simultaneous localization and mapping (SLAM) technology. The four-wheeled autonomous robot model that was utilized in the studywas created using a Jetson board with high performance processor, a depth camera, and LIDAR sensors along with ROS's RVIZ software.

关键词： Visualization Simultaneous localization and mapping Laser radar Accuracy Navigation Robot kinematics Robot vision systems

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Multi-UAVs Cooperative Pollution Source Localization Based on Improved Particle Swarm Optimization Algorithm

Multi-UAVs Cooperative Pollution Source Localization Based o...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Du, Meiyi Gao, Zhijun Yang, Liying Jiang, Han Huang, Zhaoxiong School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350316308

Accidents involving hazardous gas leakage from chemical plants occur frequently, highlighting the critical importance of accurately locating air pollution sources. Rapid localization of pollution sources through the collaborative efforts of multiple unmanned aerial vehicles (UAVs) can help prevent major disasters. To address this, this paper presents an air pollution source tracking algorithm based on an improved particle swarm optimization (IPSO) algorithm. By enhancing the inertia weight coefficient, the search efficiency and accuracy of the UAV swarm are significantly improved. The simulation environment considers a Gaussian plume model, which incorporates various atmospheric constraints such as temperature and wind speed, for UAV swarm navigation. The simulation results demonstrate that employing the particle swarm optimization algorithm to guide UAVs in locating pollution sources enables them to accurately identify the sources within a short period, exhibiting a high level of effectiveness and robustness. © 2023 IEEE.

关键词： Antennas

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A study on design and control of Omni-directional mecanum wheels based AGV system

A study on design and control of Omni-directional mecanum wh...

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International Conference on Computing and Networking Technology (ICCNT)

Automated guided vehicles (AGVs) have emerged as crucial equipment in sectors that demand reliable and effective transportation and material handling systems. The design and control features of AGV systems are discussed in general terms in this study, with an emphasis on important factors and recent developments. The vehicle platform, sensing and perception systems, navigational algorithms, and control architecture are all essential parts of the design of an AGV system. To fit the application's unique requirements, the vehicle platform must be properly developed, taking into account elements like load capacity, maneuverability, and power supply. The AGV can sense its surroundings and maneuver on its own thanks to the choice and integration of sensors including LiDAR, cameras, and encoders. Simultaneous Localization and Mapping (SLAM), one of the most sophisticated perception algorithms, is essential for precisely mapping the environment and locating the AGV within it. Because of navigation algorithms, AGVs can efficiently plan their routes, avoid dangers, and reach their targets. Methods for establishing a path enable smooth, collision-free travel by accounting for factors including distance, time, and dynamic restrictions. Real-time control systems regulate the AGV's speed, acceleration, and steering, enabling accurate and secure operation in a variety of situations. The controls design should enable monitoring of the system and detection of problems in along with enabling integration of perception, navigating, and control modules. This paper examines the mechanical and electrical design of a test prototype autonomous guided vehicle (AGV). The SLAM technique apply in the present work successfully resolves the localization problem in conjunction with the navigation algorithm.

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Backstepping-Based Adaptive Cooperative Control For Multiple Euler-Lagrange Systems Under Unknown Harmonic Disturbances

Backstepping-Based Adaptive Cooperative Control For Multiple...

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2023 China automation Congress, CAC 2023

作者： Chen, Ying Zhao, Zi-Yi Sun, Peng Guo, Xiang-Gui Wang, Jian-Liang Coutinho, Daniel School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Hangzhou Innovation Institute of Beihang University Collaborative Flying Robotics HangZhou China Universidade Federal de Santa Catarina Department of Automation and Systems Florianópolis Brazil

ISBN: (纸本)9798350303759

This paper studies cooperative control problem for multiple Euler-Lagrange systems with unknown harmonic disturbances, where the disturbances are the superposition of sinusoidal components with unknown amplitude, phase, and frequency. A novel adaptive disturbance observer without requiring the disturbance frequency information is designed to estimate the disturbances. Over the directed network topology, a cooperative control scheme is proposed based on backstepping techniques, so that the tracking error is ultimately uniformly bounded. The scheme developed can be used to reject the harmonic disturbances in a uniform way, which means the characteristics of the disturbances can be described as a fixed parameter vector. Finally, an application is presented to demonstrate the effectiveness of the proposed control strategy in the context of a two-link manipulator system. © 2023 IEEE.

关键词： Backstepping

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A new noise network and gradient parallelisation‐based asynchronous advantage actor‐critic algorithm

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IET Cyber-Systems and robotics 2022年第3期4卷 175-188页

作者： Zhengshun Fei Yanping Wang Jinglong Wang Kangling Liu Bingqiang Huang Ping Tan Provincial Key Institute of Robotics School of Automation and Electrical EngineeringZhejiang University of Science and TechnologyHangzhouChina State Key Lab of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina

Asynchronous advantage actor‐critic(A3C)algorithm is a commonly used policy opti-mization algorithm in reinforcement learning,in which asynchronous is parallel inter-active sampling and training,and advantage is a sampling multi‐step reward estimation method for computing *** order to address the problem of low efficiency and insufficient convergence caused by the traditional heuristic exploration of A3C algorithm in reinforcement learning,an improved A3C algorithm is proposed in this *** this algorithm,a noise network function,which updates the noise tensor in an explicit way is constructed to train the *** advantage estimation(GAE)is also adopted to describe the dominance ***,a new mean gradient parallelisation method is designed to update the parameters in both the primary and secondary networks by summing and averaging the gradients passed from all the sub‐processes to the main *** experiments were conducted in a gym environment using the PyTorch Agent Net(PTAN)advanced reinforcement learning library,and the results show that the method enables the agent to complete the learning training faster and its convergence during the training process is *** improved A3C algorithm has a better performance than the original algorithm,which can provide new ideas for sub-sequent research on reinforcement learning algorithms.

关键词： asynchronous advantage actorcritic (A3C) generalised advantage estimation (GAE) parallelisation reinforcement learning

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Case Study on an Experimental Autonomous Vehicle and Evaluation of its System Reliability 4

Case Study on an Experimental Autonomous Vehicle and Evaluat...

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4th International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Misaros, Marius Robier, Clement Stan, Ovidiu-Petru Enyedi, Szilard Stan, Anca Gota, Dan Ioan Miclea, Liviu Technical University of Cluj-Napoca Automation Department Cluj-Napoca Romania Cesi Ingineering School of Lyon Generalist Department Lyon France Technical University of Cluj Napoca Industrial Engineering Robotics and Production Management Romania

ISBN: (纸本)9798350391183

The ability of a vehicle to move without the input of a human operator marks its transition into the domain of the autonomous vehicle. This concept is gaining increasing popularity with the objective of enhancing navigational safety and facilitating the transmission and reception of information from other road users, thereby facilitating more efficient navigation. It was thus resolved to construct a partially autonomous vehicle that employs sensors and Li-Fi technology to receive and process external stimuli approaching the control side of the vehicle. The prototype in the proposed and analyzed case study is steered by means of a steering wheel that has been specially configured for this application and is connected by radio. Additionally, the case study examined the reliability of the vehicle, which is a crucial factor in determining the potential causes of malfunction or even complete failure of the prototype under test. The principal objective of the case study is to construct a prototype and conduct a reliability analysis of the system, examining each component to ascertain the strengths and weaknesses of the prototype under test. The findings of the study underscore the significance of assessing the hardware elements of the proposed autonomous vehicle, culminating in a favorable assessment of its reliability. © 2024 IEEE.

关键词： Reliability analysis

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