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检索条件"机构=School of Robotics and Automation Engineering"

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A Novel Software Quality Evaluation Method Based on Fuzzy Comprehensive Evaluation Model 5

A Novel Software Quality Evaluation Method Based on Fuzzy Co...

引用

5th IEEE Advanced Information Technology, Electronic and automation Control Conference, IAEAC 2021

作者： Hu, Xiaomei Li, Yilin Zhang, Mingnan Qu, Hewei Shanghai University School of Mechatronic Engineering and Automation Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200072 China

The evaluation of software quality involves many factors, therefore it is difficult to get a scientific and reasonable quantitative evaluation results. Based on the analysis of the advantages and disadvantages of AHP method and EM method, this paper proposes a fuzzy comprehensive evaluation model to evaluate the software system. The model uses the weight calculation method based on AHP-EM to overcome the defects of single weight assignment method. By evaluating the 3D visualization software system based on web, it can be seen that the evaluation result based on AHP-EM fuzzy comprehensive evaluation model is closer to the subjective evaluation conclusion than the evaluation results using single weight calculation method, which proves the validity and practicability of the evaluation method, and provides a useful theoretical reference for improving the software quality. © 2021 IEEE.

关键词： Visualization

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Digital Twin System for Robotic Tool-replacing in Tunnel Boring Machine

Digital Twin System for Robotic Tool-replacing in Tunnel Bor...

引用

IEEE International Conference on robotics and Biomimetics

作者： Junxin Liu Jianjun Yuan Liang Du Sheng Bao School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China Shanghai Robotics Institute Shanghai University Shanghai China

Tunnel boring machine (TBM) tool-replacing robot play an important role in improving the efficiency and safety of tunnel construction. However, considering the complexity and specificity of the working environment, current robotic tool-replacing solutions still have deficiencies, including the lack of customized motion simulation tools, the difficulty of human-robot interaction due to confined space, and the lack of management of robot operation data. To address these issues, this paper designs a digital twin system for robotic tool-replacing in TBM. The system builds a virtual working environment using Unity3D, and establishes a kinematic model of the robot to achieve the pre-planning of the movement trajectory. The synchronous mapping between the digital model of the robot and the physical entity is achieved through Socket communication technology, thus realizing the digital monitoring of the tool-replacing process. In addition, twin databases of the system are built based on SQLite for storing and managing the robot's operation data. Finally, the effectiveness of each functional module of the system is proved through experiments.

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An adaptive Kalman filter for physiological tremor suppression in robot-assisted minimally invasive surgery

An adaptive Kalman filter for physiological tremor suppressi...

引用

IEEE International Conference on robotics and Biomimetics

作者： Daolong Yang Li Jiang Kun Xu Robotics Institute of School of Mechanical Engineering and Automation Beihang University (BUAA) Beijing China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Physiological tremors of surgeons’ hands bring vibration to the tip of surgical instruments, which may severely damage the accuracy of surgical procedures and even put patients’ lives at risk. Thus robot-assisted surgery using a teleoperation system was introduced to solve this problem. Many filter algorithms were implemented into the robot-assisted surgery system to suppress the inevitable tremors, but always overlooking the traits of hand motion. An innovation/residual-based floating forgetting-factor adaptive Kalman filter (IFFAKF) is proposed to address this problem. A floating forgetting-factor is brought into the innovation/residual-based adaptive estimation algorithm to adjust the process noise covariance (Q) and measurement noise covariance (R) of the system, thus generating estimation of voluntary hand movement and suppressing the vibration at the tip of the surgical instrument caused by the physiological tremor during surgeries. The proposed filter has been contrasted with various filters in simulations and experiments. The results confirm that the proposed filter has obvious advantages in terms of time delay, estimation error, and tremor suppression performance.

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Simulation and implementation of deep learning based expression recognition

Simulation and implementation of deep learning based express...

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2024 International Conference on Mechatronic engineering and Artificial Intelligence, MEAI 2024

作者： Qin, Lijuan Wang, Shiyi Chen, Jiayu School of Information Science and Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (纸本)9781510689176

Facial expressions are a challenging area in image recognition, and ensuring the universality of the model in the presence of a large sample size is a difficult point in such research. This article conducts repeatability experiments on two extreme scenarios: high-quality small samples and low-quality large samples, to explore solutions. Through transfer learning, data augmentation, and substantive evaluation of confusion matrices, the article demonstrates the accurate classification of seven facial expressions and the design of a 4-class model with high universality, which is presented in the form of an APP. © 2025 SPIE.

关键词： Deep learning

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Research on Key Algorithms of Visual Simulation System for Surface Dust Concentration in Virtual Campus 5

Research on Key Algorithms of Visual Simulation System for S...

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5th IEEE Advanced Information Technology, Electronic and automation Control Conference, IAEAC 2021

作者： Hu, Xiaomei Zhang, Mingnan Li, Yilin Yu, Hefang Shanghai University Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai200072 China

ISBN: (纸本)9781728180281

In the visual simulation of surface dust concentration in virtual campus, the concentration data of each grid point should be obtained. Because the surface dust concentration data grid points are unknown, so through the discrete sample point grid points around the known surface dust concentration properties of the unknown point grid point value interpolation estimation. Therefore, it is very important to select an interpolation algorithm that can satisfy the requirement of the accuracy of the surface dust concentration and have high computational efficiency in the interpolation process of unknown points. According to the data characteristics of virtual campus surface dust concentration value, this paper proposes an inverse distance mixed interpolation algorithm for interpolation by combining the advantages of the inverse distance weighted interpolation method and the kriging interpolation algorithm, and compares the calculation results of inverse distance mixed interpolation with the traditional interpolation algorithm. The results show that inverse distance mixed interpolation algorithm not only has high accuracy, but also runs efficiently. © 2021 IEEE.

关键词： Interpolation

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Medical Image Recognition Based on Improved Convolutional Neural Network 10th

Medical Image Recognition Based on Improved Convolutional Ne...

引用

10th International Workshop of Advanced Manufacturing and automation, IWAMA 2020

作者： Zhou, Chuanhong Zhang, Yiyang Yang, Lihua School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China

ISBN: (纸本)9789813363175

As people's work pressure gradually increases, more and more people are at risk of getting sick. Doctors use CT images to diagnose the patient's disease. Since there are hundreds of CT images for a complete disease and the key CT images used to illustrate the disease are mainly a few. That is why the problem of image redundancy is highlighted. As a result, the workload of doctors has greatly increased. Therefore, solutions are urgently needed to help quickly identify medical CT images. This paper studies medical image recognition based on convolutional neural networks. Taking dental CT images as an example, the image which is most similar to the key template image is identified through the improved network model of fused feature vectors. Based on this, a platform suitable for all medical CT image recognition has been initially implemented. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image recognition

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PIPE-VINS: A Robust, Real-time Visual-Inertial State Estimator in Pipe Environment

PIPE-VINS: A Robust, Real-time Visual-Inertial State Estimat...

引用

IEEE International Conference on robotics and Biomimetics

作者： Yiming Huang Jianjun Yuan Liang Du Sheng Bao Zhengtao Hu Hongkai Zhang Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Robotics Institute Shanghai University Shanghai China

The detection and assessment of pipeline damage constitute crucial steps in pipeline maintenance. Typically, internal pipeline robots extract and track feature points under actively illuminated conditions to accomplish state estimation. However, unstable lighting within pipelines can lead to poor feature tracking performance, resulting in localization divergence. In this paper, we propose a multi-feature tracking approach that, in addition to extracting a certain number of Shi-Tomasi corners, also extracts highly efficient FAST corners to maintain feature uniqueness and expedite extraction efficiency. Moreover, we introduce a bidirectional optical flow method that performs reverse optical flow tracking on top of the existing forward tracking, thereby eliminating outliers from failed tracking and enhancing the stability of optical flow tracking. A segmented optimization approach is used during the back-end optimization process to conserve computational resources and speed up the optimization process for the variables. The proposed method is integrated into the state-of-the-art visual-inertial SLAM system, VINS-Mono, and evaluated on public datasets and pipeline datasets. Compared to other methods, our approach demonstrates matching or superior performance in terms of localization accuracy and robustness.

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Design and Analysis of ASRS Using AGV for Rapid Inventory Storage System 2nd

Design and Analysis of ASRS Using AGV for Rapid Inventory St...

引用

2nd International Conference on Mechanical engineering Design, ICMechD 2019

作者： Nair, Pranav Santhosh Nair, Sourabh Sarkar, Soukhin Arockia Doss, Arockia Selvakumar Dinakaran, D. School of Mechanical Engineering Vellore Institute of Technology Chennai India Centre for Robotics and Automation HITS Chennai India

ISBN: (纸本)9789811547447

Non-competitive market pricing is easy to use and maintain but it is a major issue in automated guided vehicles (AGVs) that are available in the current market. Space is a very valuable commodity in urban areas. The current AGV available in the market needs optimization and is specifically designed for one particular form of storage system. In order to reduce the complexity of the system, hard locating method approach is used. Hard locating is a process that assists the operator in avoiding mistakes. In this work, an AGV for rapid inventory storage system is proposed. The AGV consists of a 5-degrees of freedom (DOF) robotic arm with a two-fingered gripper is used for picking and placing the boxes. The gripper is equipped with a piezoelectric sensor to sense the size of the object. By using this approach, the existing rack can be used without much alteration. This system has the capability to increase the utilization of the warehouse. This paper presents an optimized automated storage and retrieval system (ASRS) with the help of AGV with reduced cost and complexity. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Automated guided vehicle Automated storage and retrieval system Piezoelectric sensor Warehouse optimization

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Carbon-aware Optimal Renewable Investment under Uncertainty: A Prospect Theory Analysis

Carbon-aware Optimal Renewable Investment under Uncertainty:...

引用

IEEE General Meeting Power& Energy Society

作者： Qisheng Huang Jianwei Huang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Shenzhen China

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

In this paper, we investigate the power generation company’s renewable investment problem under renewable uncertainty within the framework of the cap-and-trade policy. This policy regulates the carbon emission levels of such companies by assigning them carbon emission quotas. Previous studies on renewable investment within the cap-and-trade policy framework have predominantly concentrated on solving the expected cost-minimization problem for a risk-neutral consumer using the expected utility theory (EUT). However, empirical evidence suggests that the EUT model may not accurately reflect real-world behaviors. To address this, we propose a prospect theory (PT) model from behavioral economics to gain deeper insight into the power generation company’s renewable investment decisions, taking into account their risk preferences. Despite the non-convexity of the PT-based optimization problem of the power generation company, we obtain the optimal solutions by leveraging the unimodal structure of the objective function. Theoretical and numerical results demonstrate that the power generation company’s decisions are significantly affected by their risk preferences: 1) the PT power generation company with a higher reference point is more willing to take risks and invest in renewable energy due to the greater expectations compared with the case of a low reference point; 2) the PT power generation company is more willing to invest in renewable energy when the probability of high renewable production is small, due to the probability distortion.

关键词： Renewable energy sources Uncertainty Utility theory Companies Emissions trading Carbon dioxide Production Power generation Optimization Investment

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A multi-objective optimization trajectory interpolation method based on fifth-degree B-spline curves *

A multi-objective optimization trajectory interpolation meth...

引用

IEEE International Conference on robotics and Biomimetics

作者： Qiang Yang Xiaomeng Hu Liang Du Sheng Bao Jianjun Yuan Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Robotics Institute Shanghai University Shanghai China

With the increasing use of special-purpose robots with heavy load requirements in narrow and critical environments , the operation safety and collision avoidance of such robots have become closely related, making trajectory planning an important research direction today. This paper proposes a path points interpolation method suitable for generating multi-objective optimized motion trajectories for specific tasks, thereby improving the overall performance of the robot, especially its operational manipulability. It mainly focuses on the joint space of the robot, optimizing its velocity, acceleration, position, and force. We use two evaluation functions to compare the performance of the modified B-spline method, and employ a genetic algorithm to find the best solution. Simulation and experimental demonstrations are conducted to validate the effectiveness of the trajectory optimization. The trajectory interpolation method we proposed can optimize various performance aspects of the robot while also providing a wider range of optimization options.

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