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Bioinspired approach-sensitive neural network for collision detection in cluttered and dynamic backgrounds

APPLIED SOFT COMPUTING 2022年 122卷

作者： Huang, Xiao Qiao, Hong Li, Hui Jiang, Zhihong Chinese Minist Educ Adv Innovat Ctr Intelligent Robots & Syst Sch Mechatron Engn Key Lab Biomimet Robots SystBeijing Inst Technol Beijing 100081 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Rapid, accurate and robust detection of looming objects in cluttered moving backgrounds is a significant and challenging problem encountered when designing robotic visual systems to perform collision detection and avoidance tasks. Inspired by the neural circuit involved in the elementary motion vision of the mammalian retina, this study proposes a bioinspired approach-sensitive neural network (ASNN). The three main contributions of this work are as follows. First, a direction-selective visual processing module is built based on the spatiotemporal energy framework, which can estimate motion direction accurately via only two mutually perpendicular spatiotemporal filtering channels. Second, a novel approach-sensitive neural network is modeled as a push-pull structure formed by ON and OFF pathways, which responds strongly to approaching motion, but is insensitive to lateral motion. Finally, a method of direction-selective inhibition is introduced, which is able to effectively suppress translational backgrounds. Extensive synthetic and real robotic experiments indicate that the proposed model is able to not only detect collisions accurately and robustly in cluttered and dynamic backgrounds but also extract additional information on the approaching object, such as position and direction, which is critical for guiding rapid decision making. (C)& nbsp;2022 Published by Elsevier B.V.

关键词： Visual collision detection Bioinspiration Approach -sensitive neural network Spatiotemporal energy model

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Cooperative Filtering with Range Measurements: A Distributed Constrained Zonotopic Method

arXiv

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arXiv 2023年

作者： Ding, Yu Cong, Yirui Wang, Xiangke Cheng, Long College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This article studies the distributed estimation problem of a multi-agent system with bounded absolute and relative range measurements. Parts of the agents are with high-accuracy absolute measurements, which are considered as anchors;the other agents utilize low-accuracy absolute and relative range measurements, each derives an uncertain range that contains its true state in a distributed manner. Different from previous studies, we design a distributed algorithm to handle the range measurements based on extended constrained zonotopes, which has low computational complexity and high precision. With our proposed algorithm, agents can derive their uncertain range sequentially along the chain topology, such that agents with low-accuracy sensors can benefit from the high-accuracy absolute measurements of anchors and improve the estimation performance. Simulation results corroborate the effectiveness of our proposed algorithm and verify our method can significantly improve the estimation accuracy. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi agent systems

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Kinematics Analysis of a Manipulator for the Power Transmission Line Maintenance Robot

Kinematics Analysis of a Manipulator for the Power Transmiss...

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Chinese control Conference (CCC)

作者： Minghao Chen En Li Feng Zhang Rui Guo Zize Liang Yuwei Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Shandong Luneng Intelligence Technology Co. Ltd. Jinan China The State Grid Shandong Electric Power Company Jinan China

With the remarkable development of the power grid, traditional manual maintenance modes cannot meet the requirement of efficiency and reliability. Robotic technology is applied for power line maintenance to bring down risks and ensure inspectors' safety. Based on the power transmission line maintenance platform, a 5-DOF manipulator is designed to perform the maintenance tasks for the quad bundle conductors. Then the kinematics analysis of the manipulator is analyzed. The manipulator doesn't meet the Pieper criterion. So an improved adaptive particle swarm optimization (APSO) is proposed for figuring out the inverse kinematics. The weights of the pose and the constraint of the prismatic joint are introduced to the algorithm. What's more, half of the particles are initialized around the incipient value of joints and half of the particles are randomly initialized with the constraint of joints in this algorithm. Results show that the manipulator is able to work in the environment of quad bundle conductors and the proposed algorithm can improve the precision of inverse kinematics and prevent the leap of joints.

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RailNet: An Information Aggregation Network for Rail Track Segmentation

RailNet: An Information Aggregation Network for Rail Track S...

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International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Li, Haoran Zhang, Qichao Zhao, Dongbin Chen, Yaran Chinese Acad Sci Inst Automat Univ Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing Peoples R China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169262

As the basis of scenes understanding for the track inspection task, track segmentation is challenging due to the various illumination conditions, track crossing, and plant coverage. Since the rail has a strong shape prior, strict rail spacing and special distribution in the image, making full use of the spatial information of the rail features becomes an important factor to improve the accuracy of rail segmentation. In this paper, an information aggregation module is proposed to enhance the spatial relationship between pixels of the rail features. In other words, this module expands the receptive field. Furthermore, we build an information aggregation network based on this module, which is called as RailNet. Finally, the RailNet is evaluated in an open train track dataset. Experimental results show that RailNet can achieve the best performance so far in the dataset of trains.

关键词： Radar tracking Convolution Image segmentation Rails Shape Feature extraction Aggregates

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Research of Simulation Test Based on Parallel High-speed Train systems

Research of Simulation Test Based on Parallel High-speed Tra...

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2021 China Automation Congress, CAC 2021

作者： Dong, Sheng Zhu, Fenghua Cheng, Yuan Lv, Yisheng Liu, Jun Xiong, Gang State Key Laborotory of Control and Management for Complex Systems Institute of Autamation Chinese Academy of Sciences Beijing100190 China School of Civil and Transportation Engineering Ningbo University of Technology Ningbo315211 China China Academy of Railway Sciences Corporation Limited Beijing100081 China

ISBN: (纸本)9781665426473

High-speed train possesses high capacity, high speed, low consumption, low pollution, and it has become the development tendency of rail transportations. Parallel high-speed train provides the basic idea for constructing the transportation scenes for evaluation experiments and provides feasible approaches for carrying out experiments for evaluating the control plans of high-speed trains. The simulation test based on parallel high-speed train systems is proposed. First, the rule base is set up to model the influence of the environment for parallel high-speed train systems based on the simple-is-consistent principle. Second, the typical functions and the relations between the elements of the control system of the trains are analyzed. Third, the models of the typical operating scenes of the control systems of high-speed trains are established. Finally, the method for designing experiments for parallel high-speed train systems are studied and the operational mechanisms of parallel high-speed train systems are established. © 2021 IEEE

关键词： control systems

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Nonlinear model predictive position control for a tail-actuated robotic fish

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NONLINEAR DYNAMICS 2020年第4期101卷 2235-2247页

作者： Zhang, Pengfei Wu, Zhengxing Meng, Yan Tan, Min Yu, Junzhi Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Dept Mech & Engn Sci Coll Engn State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China

Position control is a significant technique for the underwater application of robotic fish;however, it is also very challenging due to the underactuated property and input coupling of system dynamics. In this article, a two-stage orientation-velocity nonlinear model predictive controller is proposed to solve this problem. A scaled averaging model of tail-actuated robotic fish is constructed at first. Then, the novel strategy based on orientation and velocity control is developed as well as proved to be equivalent with position control in the sense of Lyapunov. Furthermore, a nonlinear model predictive controller with a two-stage switching strategy is designed to regulate the orientation and velocity error. Finally, the simulation results demonstrate the superiority of the proposed control algorithm compared with other methods. Particularly, there exists an interesting twist-braking behavior in simulation, which indicates that the proposed method makes better use of the system dynamics. The proposed method is efficient for not only bionic robotic fish but also other aquatic underactuated robots, which offers new insight into the position control of underwater robots.

关键词： Bionic robotic fish Position control Nonlinear model predictive control Underactuated dynamics

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Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning systems

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IEEE INTERNET OF THINGS JOURNAL 2022年第6期9卷 4788-4798页

作者： Wang, Xiao Zhu, Yushan Han, Shuangshuang Yang, Linyao Gu, Haixia Wang, Fei-Yue China Nucl Power Engn Co Ltd State Key Lab Nucl Power Safety Monitoring Techno Shenzhen 518172 Guangdong Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China Zhejiang Univ Sch Comp Sci Hangzhou 310027 Peoples R China Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Technol Changsha 410073 Peoples R China Macau Univ Sci Technol Inst Syst Engn Macau Peoples R China

In recent years, deep learning (DL) has been widely used in vehicle misbehavior detection and has attracted great attention due to its powerful nonlinear mapping ability. However, because of the large number of network parameters, the training processes of these methods are time consuming. Besides, the existing detection methods lack scalability;thus, they are not suitable for Internet of Vehicles (IoV) where new data are constantly generated. In this article, the concept of the broad learning system (BLS) is innovatively introduced into vehicle misbehavior detection. In order to make better use of vehicle information, key features are first extracted from the collected raw data. Then, a BLS is established, which is able to calculate the connection weight of the network efficiently and effectively by ridge regression approximation. Finally, the system can be updated and refined by an incremental learning algorithm based on the newly generated data in IoV. The experimental results show that the proposed method performs much better than DL or traditional classifiers, and could update and optimize the old model fastly and progressively while improving the system's misbehavior detection accuracy.

关键词： Convolutional neural networks Feature extraction Machine learning algorithms Deep learning Global Positioning System Scalability Safety Broad learning system (BLS) incremental learning system Internet of Vehicles (IoV) misbehavior detection ridge regression approximation

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Boosting Black-Box Adversarial Attacks with Meta Learning

arXiv

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arXiv 2022年

作者： Fu, Junjie Sun, Jian Wang, Gang The State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

Deep neural networks (DNNs) have achieved remarkable success in diverse fields. However, it has been demonstrated that DNNs are very vulnerable to adversarial examples even in black-box settings. A large number of black-box attack methods have been proposed to in the literature. However, those methods usually suffer from low success rates and large query counts, which cannot fully satisfy practical purposes. In this paper, we propose a hybrid attack method which trains meta adversarial perturbations (MAPs) on surrogate models and performs black-box attacks by estimating gradients of the models. Our method uses the meta adversarial perturbation as an initialization and subsequently trains any black-box attack method for several epochs. Furthermore, the MAPs enjoy favorable transferability and universality, in the sense that they can be employed to boost performance of other black-box adversarial attack methods. Extensive experiments demonstrate that our method can not only improve the attack success rates, but also reduces the number of queries compared to other methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep neural networks

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Near-infrared fluorescence imaging with an MET-targeting probe for biopsy site selection in patients with oral potentially malignant disorders

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CELL REPORTS MEDICINE 2025年第3期6卷 101978-101978页

作者： Wang, Jingbo Shen, Xuemin Ma, Qifan Yang, Lin Zhou, Xiaoyu Wang, Luting Cui, Junqi Zhang, Chunye Li, Guojun Gross, Neil Li, Siyi Huang, Ruimin Zhan, Changyou Cheng, Zhen Wang, Kun Tian, Jie Yuan, Ying Tao, Xiaofeng Shanghai Jiao Tong Univ Shanghai Peoples Hosp 9 Sch Med Dept Radiol Shanghai 200011 Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples Hosp 9 Sch Med Dept Oral Mucosal DisColl Stomatol Shanghai Peoples R China Natl Clin Res Ctr Oral Dis Shanghai Key Lab Stomatol Shanghai 200011 Peoples R China Shanghai Res Inst Stomatol Shanghai 200011 Peoples R China Fujian Childrens Hosp Fujian Branch Shanghai Childrens Med Ctr Dept Radiol Fujian 350014 Peoples R China Chinese Acad Sci Shanghai Inst Mat Med Mol Imaging Ctr State Key Lab Drug Res Shanghai 201203 Peoples R China Shanghai Jiao Tong Univ Sch Med Shanghai Peoples Hosp 9 Dept Pathol Shanghai 200011 Peoples R China Univ Texas MD Anderson Canc Ctr Dept Head & Neck Surg Houston TX 77030 USA Shanghai Jiao Tong Univ Shanghai Peoples Hosp 9 Coll Stomatol Dept Oral & Maxillofacial Head & Neck OncolSch M Shanghai 200011 Peoples R China Chinese Acad Sci Ctr Drug Safety Evaluat & Res Shanghai Inst Mat Med Shanghai 201203 Peoples R China Fudan Univ Sch Basic Med Sci Dept Pharmacol Shanghai 200433 Peoples R China Fudan Univ Shanghai Pudong Hosp Ctr Med Res & Innovat Shanghai 200433 Peoples R China Fudan Univ State Key Lab Mol Engn Polymers Shanghai 200433 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst CAS Key Lab Mol Imaging Beijing Key Lab Mol ImagingInst Automat Beijing 100190 Peoples R China

Accurate detection of malignant transformation in oral potentially malignant disorders (OPMDs) is crucial for guiding effective treatment and improving patient management. This study evaluates the potential of MET- binding peptide-indocyanine green (cMBP-ICG), a mesenchymal-epithelial transition factor (MET)-targeted near-infrared fluorescence imaging (NIRFI) probe, for biopsy site selection in OPMDs. Preclinical results demonstrate the superior accuracy of NIRFI-assisted biopsy over conventional oral examination (COE)based biopsy in detecting high-grade dysplasia (HGD) or squamous cell carcinoma (SCC) and reducing missed detection rates. In a clinical trial with 50 patients, NIRFI-assisted biopsy achieves significantly higher diagnostic accuracy compared to COE-based biopsy (91% vs. 72%, p = 0.0005). These findings underscore the importance of NIRFI in enhancing diagnostic precision, supporting early detection and enabling timely and accurate treatment interventions for patients with OPMDs. The clinical trial is registered under the registration number ChiCTR2300074454.

关键词： oral squamous cell carcinoma oral potentially malignant disorders mesenchymal-epithelial transition factor near-infrared targeted fluorescent imaging topical application biopsy site selection fluorescence-guided biopsy 4-NQO-induced OSCC model molecular imaging

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Gliding Motion Regulation of a Robotic Dolphin Based on a controllable Fluke

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2020年第4期67卷 2945-2953页

作者： Wu, Zhengxing Yu, Junzhi Yuan, Jun Tan, Min Qi, Suwen Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Peking Univ Coll Engn State Key Lab Turbulence & Complex Syst Dept Mech & Engn SciBIC ESAT Beijing 100871 Peoples R China Shenzhen Univ Sch Med Dept Biomed Engn Shenzhen 518060 Peoples R China

This paper investigates a controllable fluke's regulation effect on the gliding motion of a self-propelled robotic dolphin in both theory and practice. In theory, based on a dynamic model, the gliding equilibria is first analyzed. Through deriving the explicit expressions of the pitch angle, gliding angle, and velocities, we explore how the deflection angle of the controllable fluke changes the gliding performance. Then, aided by these theoretical analyses, a pitch control strategy relying on the fluke is constructed. In simulations, the robotic dolphin is able to track a given pitch angle during gliding, directly through adopting this control strategy to regulate the fluke's deflection angle. Furthermore, extensive gliding experiments in different fluke's deflection angles are carried out. From the statistical data, we further explore the remarkable effects of the controllable fluke on the gliding performance in practice. Besides, the other pitch control experiment is also executed to validate the effectiveness of the proposed control approach. The results of this paper shed light on improving the gliding performance of the robotic dolphin in future mechanical design and gliding control.

关键词： Gliding robotic dolphin motion control pitch control underwater robotics

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