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2024 International Conference on Image, Signal processing, and Pattern Recognition, ISPP 2024

作者： Wang, Zhongbo He, Miao Ding, Qinghai Luo, Haibo Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Space Star Technology Co Ltd. Beijing100086 China

ISBN: (纸本)9781510680425

Synthetic aperture radar (SAR) is an essential tool for ocean *** the main participants on the ocean, ships are the most important targets for ocean *** it is of great importance to develop ship detection algorithms for SAR sea *** algorithms based on Convolutional Neural Network perform far better than the traditional methods based on manual features on ship detection task due to the powerful feature representation *** algorithms based on Convolutional Neural Network can be divided into one-stage algorithms, and two-stage ***-stage algorithms have high accuracy, but are relatively ***-stage algorithms have high inference speed, but compared with two-stage algorithms, they have lower *** in this article, we proposed an modified one-stage detection algorithm to improve the accuracy of ship detection in a condition that the modified algorithm meet the real-time ***, the small model of one-stage algorithm YOLOV5 is chosen as the base network to get the high inference ***, to improve the accuracy of ship detection with a little increase in inference time and the model parameters, we integrate the one-layer super-resolution architecture with the simplist structure into the YOLOV5 ***, we conducted the comparative experiments on our Dataset to verify the performance of modified YOLO *** experimental results show that the modified method has obtained an Average Precision (AP) improvement than the original YOLO V5 for detecting ships in SAR images with a little increase in inference time and the model parameters. © 2024 SPIE.

关键词： Convolutional neural networks

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Multi-stage Objective Function Optimized Hand-Eye Self-calibration of Robot in Autonomous Environment 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Liu, Kaibo Zheng, Wangli Min, Huasong Lin, Yunhan School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Hubei Wuhan430065 China State Grid Electric Power Research Institute Jiangsu Nanjing211106 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Hubei Wuhan430081 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

In the application scenario of robot autonomous tasks, the robot needs to be able to complete calibration online and automatically to achieve self-maintenance, which differs from traditional robot hand-eye calibration in that the traditional robot hand-eye calibration requires a dedicated calibration board to assist offline completion. Aiming at the problem that the existing self-calibration methods cannot be optimized as a whole, which leads to low accuracy and instability of the solution, a multi-stage objective function optimization self-calibration algorithm is proposed, which describes the solution of hand-eye self-calibration as a minimization objective function problem involving multiple stages. An optimization method based on the minimization of re-projection error is designed to compensate for the results, which uses an efficient Oriented fast and rotated brief (ORB) feature extraction algorithm and introduces a scoring mechanism to retain more correct matching points in the feature matching stage. Two different types of experiments were designed to validate our method. One is a single camera dataset experiment, which shows that our method is more accurate and robust than the existing self-calibration method;the other is an application platform experiment, which verifies the feasibility and availability of our method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Calibration

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An Interactive Navigation Method with Effect-oriented Affordance

An Interactive Navigation Method with Effect-oriented Afford...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiaohan Wang Yuehu Liu Xinhang Song Yuyi Liu Sixian Zhang Shuqiang Jiang Institute of Artificial Intelligence and Robotics Xi’ an Jiaotong University Xi'an Key Lab of Intelligent Information Processing Laboratory of the Chinese Academy of Sciences (CAS) Institute of Computing Technology Beijing University of Chinese Academy of Sciences Beijing

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Visual navigation is to let the agent reach the target according to the continuous visual input. In most previous works, visual navigation is usually assumed to be done in a static and ideal environment: the target is always reachable with no need to alter the environment. However, the “messy” environments are more general and practical in our daily lives, where the agent may get blocked by obstacles. Thus Interactive Navigation (InterNav) is introduced to navigate to the objects in more realistic “messy” environments according to the object interaction. Prior work on InterNav learns shortterm interaction through extensive trials with reinforcement learning. However, interaction does not guarantee efficient navigation, that is, plan-ning obstacle interactions that make shorter paths and con-sume less effort is also crucial. In this paper, we introduce an effect-oriented affordance map to enable longterm interactive navigation, extending the existing map-based nav-igation framework to the domain of dynamic environment. We train a set of affordance functions predicting available interactions and the time cost of removing obstacles, which informatively support an interactive modular system to ad-dress interaction and longterm planning. Experiments on the ProcTHOR simulator demonstrate the capability of our affordance-driven system in longterm navigation in complex dynamic environments.

关键词： Visualization Computer vision Uncertainty Costs Navigation Affordances Reinforcement learning

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Soft robotics:Morphology and Morphology-inspired Motion Strategy

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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PL-TD3: A Dynamic Path Planning Algorithm of Mobile Robot

PL-TD3: A Dynamic Path Planning Algorithm of Mobile Robot

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Tan, Yijian Lin, Yunhan Liu, Tong Min, Huasong Wuhan University of Science and Technology College of Computer Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

In this paper, Prioritized Experience Replay (PER) strategy and Long Short Term Memory (LSTM) neural network are introduced to the path planning process of mobile robots, which solves the problems of slow convergence and inaccurate perception of dynamic obstacles with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. We dubbed this new method as PL-TD3. Firstly, we improve the convergence speed of the algorithm by introducing PER strategy. Secondly, we use LSTM neural network to achieve the improvement of the algorithm for dynamic obstacle perception. In order to verify the method of this paper, we design static environment, dynamic environment and adaptability to dynamic experiments to compare and analyze the methods before and after improvement. The experimental results show that PL-TD3 outperforms TD3 in terms of execution time and execution path length in all environments. © 2022 IEEE.

关键词： Motion planning

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Generating Manipulation Sequences using Reinforcement Learning and Behavior Trees for Peg-In-Hole Task

Generating Manipulation Sequences using Reinforcement Learni...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Xu, Jiahua Lin, Yunhan Zhou, Haotian Min, Huasong Wuhan University of Science and Technology College of Computer Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Reinforcement Learning (RL), a method of learning skills through trial-and-error, has been successfully used in many robotics applications in recent years. We combine manipulation primitives (MPs), behavior trees (BTs), and reinforcement learning to propose an algorithm for peg-in-hole tasks, which speeds up the convergence of the RL model and enhance the adaptability of the dynamic environment. Manipulation primitives are used as actions for RL, which can reduce the gap between control instruction and robotic actions and speed up the convergence of the RL model. Behavior trees are used as robot behavior control, which makes robots can actively adapt to the changes in the environment. In experiments, RL-BT, from the combination of RL and BT, is designed for the peg-in-hole task in the Gazebo simulation environment by using UR5 as the actuator. The experiments are conducted on a simple peg and a complex multi-hole peg by three aspects, which include convergence speed verification experiment, adaptability of dynamic environment experiment, and algorithm robustness experiment. The experiment result proves that our RL-BT can speed up the convergence and adapt to the changes in the environment. © 2022 IEEE.

关键词： Reinforcement learning

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Adjacency-hopping de Bruijn Sequences for Non-repetitive Coding

arXiv

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arXiv 2023年

作者： Chen, Bin Liang, Zhenglin Wu, Shiqian The Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430081 China The Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430072 China

A special type of cyclic sequences named adjacency-hopping de Bruijn sequences is introduced in this paper. It is theoretically proved the existence of such sequences, and the number of such sequences is derived. These sequences guarantee that all neighboring codes are different while retaining the uniqueness of subsequences, which is a significant characteristic of original de Bruijn sequences in coding and matching. At last, the adjacency-hopping de Bruijn sequences are applied to structured light coding, and a color fringe pattern coded by such a sequence is presented. In summary, the proposed sequences demonstrate significant advantages in structured light coding by virtue of the uniqueness of subsequences and the adjacency-hopping characteristic, and show potential for extension to other fields with similar requirements of non-repetitive coding and efficient matching. Copyright © 2023, The Authors. All rights reserved.

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A Deep Ship Recognition Model Based on Multi-category Fusion of General Datasets 6

A Deep Ship Recognition Model Based on Multi-category Fusion...

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6th IEEE International Conference on Civil Aviation Safety and information Technology, ICCASIT 2024

作者： Su, Hang Qiu, Guoping Dongguan University of Technology School of Telecommunications Engineering and Intelligentization Guangdong Dongguan523808 China College of Electronic and Information Engineering Shenzhen University Guangdong Shenzhen518060 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Guangdong Shenzhen518060 China Shenzhen University Branch Shenzhen Institute of Artificial Intelligence and Robotics Guangdong Shenzhen518060 China Shenzhen University Shenzhen Key Laboratory of Digital Creative Technology Guangdong Shenzhen518060 China

ISBN: (纸本)9798350389418

To meet the demand for accurate and rapid recognition of ship targets in existing ship image recognition methods, this study applies the DCNN model, known for its powerful feature extraction capabilities, to the task of ship image recognition. To enhance the model's performance, a novel dataset fusion training method is utilized. The DCNN model requires large-scale labeled training datasets;however, there is currently a lack of diverse and large-scale labeled ship image datasets in the public domain. Additionally, manually collecting and labeling large-scale ship recognition data is labor-intensive. Therefore, this paper proposes a new approach by creating a ship target recognition dataset that fuses existing general datasets for training the ship recognition model. Furthermore, a model training method that integrates multi-category image recognition is proposed. In this method, a focal loss-based optimization training approach is specifically employed to handle imbalanced data classification, thereby improving the recognition performance of ship images within multi-category datasets. Performance tests on the trained model show that the mean Average Precision (mAP) of the model trained with multi-category fusion is relatively improved by 9.45 % compared to the 3 8. 1 9 % mAP of the model trained without focal loss on a single category. Experimental results demonstrate that the proposed multi-category image training method can effectively enhance the performance of ship image recognition tasks in training using existing general image recognition datasets. © 2024 IEEE.

关键词： Convolutional neural networks

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SMA: A Suitable-Matching Area Selection Dataset 7

SMA: A Suitable-Matching Area Selection Dataset

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7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Jiang, Supeng Liu, Yunpeng Zou, Depeng Qin, Hengjia Luo, Haibo Key Laboratory Of Opto-Electronic Information Processing Chinese Academy Of Sciences Shenyang110016 China Shenyang Institute Of Automation Chinese Academy Of Sciences Shenyang110016 China Institutes For Robotics And Intelligent Manufacturing Chinese Academy Of Sciences Shenyang110169 China University Of Chinese Academy Of Sciences Beijing100049 China The Third Military Representative Office Of The Air Force Equipment Department In Shenyang Shenyang110016 China

ISBN: (纸本)9798350361445

Scene matching is a commonly used guidance technology in the final guidance stage of missiles. Suitable-matching area selection is the core technology of reference map preparation and one of the critical factors affecting the performance of the scene-matching system. Since there is no public dataset for scene-matching suitable area selection, it is difficult to compare related selection algorithms uniformly. In this paper, we analyze the scene categories that may be encountered in the scene-matching process and create a dataset SMA, which contains six scene types and various scene contents. This dataset can be used for matching performance analysis and evaluation of scene areas. We analyze the information content, stability, uniqueness, and significance of the images and conduct matching experiments by simulating real-time images to prove the matching performance of the calibration area. © 2024 IEEE.

关键词： Navigation

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Impact of Air Quality on Millimeter Wave Transmission Performance 3

Impact of Air Quality on Millimeter Wave Transmission Perfor...

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3rd International Conference on Defence Technology, ICDT 2022

作者： Wu, Hongming Wang, Ningbo Wang, Yelong Wang, Jinkuan College of Information Science and Engineering Northeastern University Liaoning Province Shenyang110819 China Shenyang Institute of Automation Chinese Academy of Sciences China The Key Laboratory of Liaoning Province in Terahertz Imaging and Sensing Shenyang110169 China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China The Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110169 China

In this paper, we use millimeter wave radar to conduct outdoor experiments under different air quality conditions and analyze the degree of millimeter wave transmission attenuation. The radar we use operates at 94 GHz with a bandwidth of 1 GHz, a distance resolution of 15 cm, and a maximum detection distance of about 150 meters. We mainly use PM2.5 and PM10 indices as air quality criteria and find that the reflected signal strength of millimeter wave from 90m to 150m decreases by 0.38dB when the air quality rises from 136 to 250, indicating that the weaker the air quality, the weaker the millimeter wave signal strength. This provides an experimental basis for the field of millimeter wave communication. © Published under licence by IOP Publishing Ltd.

关键词： Air quality

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