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

作者： Zhu, Zuhao Long, Yi He, Long Lu, Yaoan Li, Jian Guo, Liangsheng College of Information Science and Engineering Northeastern University Liaoning Shenyang China Faculty of Robot Science and Engineering Northeastern University Liaoning Shenyang China Zhiyuan Research Institute Zhejiang Hangzhou China Guangdong Provincial Key Laboratory of Minimally Invasive Surgical Instruments and Manufacturing Technology Guangdong University of Technology Guangzhou China Department of Orthopaedics The Second Affiliated Hospital of Soochow University Suzhou China

ISBN: (纸本)9789819964796

In order to solve the problem of insufficient positioning accuracy in the detection process of ceramic filters, a high-precision positioning algorithm based on edge detection fitting is proposed. The algorithm combines hierarchical pyramid model to locate ceramic filter step by step and obtain ROI region. Secondly, according to the rough location results of the target area, combined with the improved Canny detection algorithm, the ceramic filter is sub-pixel extracted, and a hierarchical screening method is proposed to obtain the contour information of the circular hole, which improves the stability of the algorithm. The minimum circumscribed circle algorithm based on Tukey is used to fit the extracted sub-pixel contour by weight, and the center position of the circular hole is obtained. Finally, according to the geometric relationship between the center of the circular hole and the ceramic filter, the center coordinates and offset angle of the ceramic filter are solved. The results of the experiment demonstrate that the ceramic filter positioning algorithm described in this paper can accomplish accurate and precise positioning of ceramic filters, in which the center repeated positioning error is 1.86 pixels and the angle error is 0.1137°, which meets the requirements for the positioning accuracy of ceramic filters. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Computer vision

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Guest Editorial:Autonomous systems:Navigation,learning,and control

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IET Cyber-Systems and robotics 2021年第4期3卷 279-280页

作者： Yu Zhang Fei Gao Yuxiang Sun Naira Hovakimyan Zheng Fang College of Control Science and Engineering Zhejiang UniversityHangzhouChina Department of Mechanical Engineering The Hong Kong Polytechnic UniversityHong Kong Department of Mechanical Science and Engineering University of Illinois at Urbana‐ChampaignChampaignIllinoisUSA Faculty of Robot Science and Engineering Northeastern UniversityShenyangChina

This is the IET Cyber-systems and robotics special issue of Autonomous systems:Navigation,learning,and *** systems,as very important representatives of Artificial Intelligence technologies,combine mechanical and electronic hardware,operating system,low-level dynamic control,and high-level intelligent decision components to address challenges that demand high-level autonomy and ma-chine intelligence.

关键词： hardware learning Intelligence

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Lexicographic Multi-objective Order Picking Optimization for robotic Mobile Fulfillment Systems

Lexicographic Multi-objective Order Picking Optimization for...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Wang, Hanying Zhao, Ziyan Liang, Jiaqi Li, Xingyang Liu, Shixin College of Information Science and Engineering Northeastern University Shenyang110819 China Foshan Graduate School of Innovation Northeastern University Foshan China Polytechnique Montréal Département de Mathématiques et Génie Industriel MontréalQCH3T 1J4 Canada Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries The College of Information Science and Engineering Shenyang110819 China School of Control Engineering/School Northeastern University at Qinhuangdao Hebei Qinhuangdao066004 China

ISBN: (纸本)9781665410205

In light of advancements in artificial intelligence, the Internet of Things, and mechatronics, robots are increasingly integrated into e-commerce warehouses to enable smart order picking solutions and foster intelligent automation. A robot-assisted order picking process revolutionizes the traditional labor-intensive person-to-goods order picking technology, leading to a goods-to-person (G2P) smart warehouse. Within it, robots transport pods to predefined picking stations, where human pickers retrieve the requested goods from these pods to fulfill customer orders. The allocation of pods to robots and the scheduling of picking operations are key optimization issues in G2P order picking systems. Although they play a key role in improving operational efficiency, existing research has paid limited attention to their joint optimization. This study considers a lexicographic multi-objective optimization problem to shorten the order picking cycles under the premise of optimizing the picking efficiency evaluated by makespan. We build a mixed integer program for the newly proposed problem and develop a matheuristic algorithm by integrating a commodity-order model into a metaheuristic algorithm to solve it. Experimental results show that the proposed method can significantly shorten the total order picking cycles while keeping the minimum makespan. It outperforms a recent state-of-the-art algorithm. This work emphasizes the importance of joint optimization within G2P smart warehouses and reveals the high potential of the proposed method to be used in practice. © 2024 IEEE.

关键词： Integer programming

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Improved Label Space Alignment for Motor Imagery Classification

Improved Label Space Alignment for Motor Imagery Classificat...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Hao Li ShiGuang Wen Jing Liu Qi Wu Lu Han Fei Wang Faculty of Robot Science and Engineering Northeastern University ShenYang LiaoNing CHINA LiaoNing Disabled Persons'Service Center ShenYang LiaoNing CHINA

Motor imagery is one mode of brain-computer interface technology that can reflect person's motor intention. However, the EEG signals vary significantly over time and individuals, making it difficult to get the ideal sample data. In order to expand the sample data and make better use of multidomain data, this paper proposes a method called Improved Label Space Alignment (ILA), combined with heterogeneous transfer learning when the label space is heterogeneous. The core idea is to align with the class center of the source domain and the target domain, which includes three key steps: clustering, class matching and data alignment. We used three classification methods in binary classification heterogeneous scenario to verify our method. The results show that the improvement of ILA for the three classification methods was 20.88 %, 10.69% and 5.59%, and the effect is more obvious when the target domain labeled data is less.

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A Reinforcement Learning-Based Approach to Improve the Trajectory Generalization Performance of DMP

A Reinforcement Learning-Based Approach to Improve the Traje...

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Chinese Control Conference (CCC)

作者： Peng Yu Lijin Fang Yian Qian College of Information Science and Engineering Northeastern University Shenyang P. R. China Faculty of Robot Science and Engineering Northeastern University Shenyang P. R. China

Dynamic Motion Primitives (DMP) is a trajectory coding method based on imitation learning, which achieves a wide application owing to its robustness and generalization ability. However, the generalization of DMP in some special cases is not very satisfactory. For instance, when the target point changes, the similarity of the middle part of the trajectory is also greatly affected. Moreover, scaling the trajectory of the DMP is often followed by a reduction in endpoint accuracy. To solve the above problems, the following work is carried out in this paper: First, we reviewed the basic DMP framework and analyzed its worthy improvements. Second, the Pearson correlation coefficient is introduced to quantitatively assess the similarity of generalized trajectories. Next, a model-free, sampling-based reinforcement learning framework Path Integrals (PI 2 ) is designed for the optimization of generalized trajectories, where the Gaussian weights of the DMP are iteratively updated probabilistically. Finally, the feasibility of the method in this paper is verified by simulation in the case of target variation and trajectory scaling.

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End-to-End Two-Handed Sign Language Translation

End-to-End Two-Handed Sign Language Translation

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Haitao Yu Shiguang Wen Chuanwen Liu Zida An Binbin Wang Libo Zhang Liao Ning Jing Liu Qi Wu Lu Han Fei Wang Faculty of Robot Science and Engineering Northeastern University ShenYang LiaoNing CHINA LiaoNing Disabled Persons' Service Center ShenYang LiaoNing CHINA

Sign language recognition and translation bridges the gap between hearing-impaired people and ordinary people. Compared with sign language recognition (SLR), continuous sign language translation (CSLT) is closer to people's speaking habits, and has greater practicality. However, there are problems such as insufficient information and short pauses in continuous sentences that are difficult to separate. To solve these problems, this paper gets coarse-grained arm movement, fine-grained finger movement and hand rotation information through the MYO armband; an encoder-decoder model with attention mechanism translates in an end-to-end manner without segmentation. After a series of experiments, the best model was selected, achieving an accuracy of 94.1%.

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Enhancing Monocular 3D Object Detection with Occlusion Compensation

Enhancing Monocular 3D Object Detection with Occlusion Compe...

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Chinese Automation Congress (CAC)

作者： Yingcai Wan Qiankun Zhao Yongjie Hu Lijin Fang Faculty of Robot Science and Engineering Northeastern University Shen Yang China Luoyang Institute of Electro-Optical Equipment AVIC Luoyang China

In the context of autonomous driving, occlusion significantly impacts the accuracy of monocular 3D object detection. To address this issue, a monocular 3D detection occlusion compensation algorithm is proposed to optimize the detection results affected by occlusion. The approach involves integrating an occlusion processing module into the 3D object detection pipeline. This module analyzes and handles occluded vehicles by leveraging 2D object detection results to infer occlusion relation-ships. Subsequently, the occluded local features associated with these relationships are captured by the local feature processing module and then input to the occlusion processing network. The resulting occlusion compensation offset is fed into the 3D object detection branch. Experimental results demonstrate that the method outperforms existing approaches on the KITTI 3D object detection benchmark.

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Imperceptible and Sparse Adversarial Attacks via a Dual-Population-Based Constrained Evolutionary Algorithm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 268-281页

作者： Tian, Ye Pan, Jingwen Yang, Shangshang Zhang, Xingyi He, Shuping Jin, Yaochu Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Anhui University School of Computer Science and Technology Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Hefei230601 China Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Hefei230601 China Bielefeld University Faculty of Technology Bielefeld33619 Germany

The sparse adversarial attack has attracted increasing attention due to the merit of a low attack cost via changing a small number of pixels. However, the generated adversarial examples are easily detected in vision since the perturbation to each pixel is relatively large. To achieve imperceptible and sparse adversarial attacks, this article formulates a bi-objective constrained optimization problem, simultaneously minimizing the 0 and 2 distances to the original image, and proposes a dual-population-based constrained evolutionary algorithm to solve it. The proposed method solves the optimization problem by evolving two populations, where one population is responsible for finding feasible solutions (i.e., successful attacks) and the other one is to minimize both the 0 and 2 distances. Moreover, a population initialization strategy and two genetic operators are customized to accelerate the convergence speed. Experimental results indicate that the proposed method can achieve high success rates with low attack costs, and strikes a better balance between the 0 and 2 distances than state-of-the-art methods. © 2020 IEEE.

关键词： Evolutionary algorithms

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Fault Diagnosis of Harmonic Reducers Based On a FDG-Resnet Joint Methodology

Fault Diagnosis of Harmonic Reducers Based On a FDG-Resnet J...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Jing Lv Zhuo Long Juan Wang Xiaoguang Ma College of Electronics and Information Engineering Heilongjiang University of Science and Technology Harbin China Faculty of Robot Science Engineering and also with the Foshan Graduate School Northeastern University Northeastern University Foshan China

Harmonic reducers(HRs) are widely used in various industrial fields due to its advantages of high precision, high transmission efficiency and compact structure. However, the vibration signal of the HRs are complex, making it difficult to diagnose faults accurately. In this paper, a method based on frequency domain Gramian angular field (FDG) and Deep residual network was proposed to classify the fault states of the HRs. First, the vibration signals were converted into twodimensional images using Gramian angular field (GAF) coding, and a two-dimensional discrete Fourier transform (2D-DFT) were performed to transform the images from the spatial domain to the frequency domain; The training accuracy of traditional models is not very high due to their low number of network layers. The deep residual network not only has a very deep network layer, but also can guarantee the accuracy of the model under certain conditions, so the deep residual network is introduced to train the model. Finally, experiments were designed using data from a real industrial HRs health monitoring platform to validate the proposed method. Under fixed operating conditions, the proposed method achieved an accuracy of 99%, which was an improvement of 0.3% compared to ResNet50, 3.5% compared to VGGNet-16, and 2.9% compared to the Swin-Tiny model. Under variable load conditions, it achieved an accuracy of 99.4%, an increase of 0.7% compared to ResNet50, 5.5% compared to VGGNet-16, and 5.6% compared to Swin-Tiny. Under variable speed conditions, it achieved an accuracy of 94.3%, an improvement of 0.9% compared to ResNet50, 0.1% compared to VGGNet-16, and 9.3% compared to Swin-Tiny.

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Experimental Study on 3-DoF Motion Control of Unmanned Water-powered Aerial Vehicle Using Nozzle Rotation Mechanism

Experimental Study on 3-DoF Motion Control of Unmanned Water...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Cao-Tri Dinh Thien-Dinh Nguyen Thinh Huynh Dong-Hun Lee Yong-Woon Choi Young-Bok Kim Department of Intelligent Robot Engineering Pukyong National University Busan Korea Department of Smart Mobility Engineering Pukyong National University Busan Korea Department of Information System Science Faculty of Engineering Soka University Tokyo Japan

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Specialized missions around water bodies, such as firefighting, rescue, and exploration, always pose a challenge to operators with low visibility, dense smoke, and extreme temperatures. To minimize the potential risks that may affect the operator, this paper proposed an unmanned water-powered aerial vehicle using a nozzle rotation mechanism. This mechanism allows the vehicle to have a wide range of forces and torques in multiple directions under constant mass flowrate condition. In the control system design, a robust controller is designed to regulate the altitude, roll, and pitch motions of the vehicle. In detail, to come up with the control law, the following steps are taken. Firstly, a mathematical model is derived to reflect the vehicle dynamics. Secondly, an integral sliding mode controller is applied to control the three-degree-of-freedom motion of the vehicle. Thirdly, experiments are conducted to confirm the effectiveness and feasibility of the controller and vehicle, respectively. Moreover, a well-known proportional-derivative-integral controller is applied to compare with the proposed control system. The results demonstrate that the vehicle could fly following the desired altitude in the presence of external disturbances.

关键词： Automation 3-DOF Control systems Mathematical models Trajectory Vehicle dynamics Motion control

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