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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Feng, Qi Gu, Chaochen Qin, Jiani Xu, Rui Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665436786

Precise 6D pose estimation of the target object is an essential prerequisite for robots to understand the real world. Previous 6D pose estimation methods based on 3D data usually have problems such as long model training time, imperfect feature extraction, redundant network model parameters, and complicated follow-up processing steps. This paper proposes a 2D-3D feature fusion module that could enhance feature extraction for the 6D pose estimation network. Furthermore, we compress the size of model parameters by adopting depthwise separable convolution to accelerate training speed and to reduce memory consumption. The experiment results on LineMOD dataset show the effectiveness of our method. Our method achieves on par or better performance than the state-of-art methods for 6D pose estimation and reduces model training time and the number of model parameters simultaneously. © 2021 IEEE.

关键词： Convolution

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Enhancing the McEliece Scheme Based on Concatenation of Polar Codes and Blocked QC-LDPC Codes

Enhancing the McEliece Scheme Based on Concatenation of Pola...

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IEEE Conference on Communications and Network Security (CNS)

作者： Xin Lin Yusun Fu Zihao Wang Junpeng Yin Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350375961

ISBN: (纸本)9798350375978

This paper proposes an enhanced McEliece cryptosystem, leveraging a concatenation scheme of Polar codes and blocked QC-LDPC codes. During the key generation phase, the generator matrices for both Polar and blocked QC-LDPC codes are employed as private keys. These matrices are subsequently multiplied by reversible and random permutation matrices respectively. The products of these multiplications are then combined to form the public key, effectively concealing the structural properties of the generator matrices. In the encryption phase, the plaintext is encrypted sequentially through the Polar codes and the blocked QC-LDPC codes. This process introduces two layers of random error vectors, culminating in the generation of the encrypted ciphertext. The proposed scheme reduces the public key length by 54% and doubles the security level compared to the original McEliece scheme with similar parameters. It also significantly reduces the total key length compared to improved schemes based on Polar codes and QC-LDPC/MDPC codes at an 80-bit security level, and shortens the private key length compared to schemes based on Polar-LDPC concatenated codes. Notably, the scheme is secure against known structural and decoding attacks while increases resistance to information set decoding (ISD) attacks. Through the randomization and hashing of the plaintext, the proposed scheme can achieve IND-CCA2 security.

关键词： Resistance Codes Public key Network security Generators Vectors Decoding Encryption Concatenated codes Polar codes

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AoI-Reliability Analysis with Block Length over Erasure Channels Using Rateless Codes

AoI-Reliability Analysis with Block Length over Erasure Chan...

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International Conference on Communication Technology (ICCT)

作者： Haobo Huang Yusun Fu Yue Qiao Junpeng Yin Weiwu Yan Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

As a metric to measure the information freshness, Age of information (AoI) is widely used to evaluate low-latency high-reliability communication. Since the communication in Industrial Internet of Things (IIoT) often has the special requirements, the relationship among AoI, reliability and block length in time-critical scenarios with bounded latency and non-time-critical scenarios without bounded latency is explored respectively in this paper, based on erasure channels using rateless codes. We build a model using LT codes over erasure channels and consider two metrics: average AoI and bounded AoI. Theoretical analysis and simulation results show that AoI has a minimum value with different block lengths. Furthermore, we draw a conclusion that the minimum value of AoI under different reliability is monotonically decreasing functioned with reliability. Finally, the impact of overhead on reliability and AoI of LT codes in time-critical scenarios is studied.

关键词： Measurement Codes Simulation Reliability theory information age Communications technology Time factors Low latency communication Industrial Internet of Things

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Boltzmann Robust Soliton Distribution for Rateless Codes

Boltzmann Robust Soliton Distribution for Rateless Codes

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International Conference on Communication Technology (ICCT)

作者： Jinhui Tang Yusun Fu Yue Qiao Junpeng Yin Haobo Huang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

The decoding success rate may be worse when classical degree distributions are used in short-packet transmission of rateless codes, especially in industrial communication scenarios. A novel Boltzmann degree distribution is proposed for Luby Transform (LT) codes. The Boltzmann degree distribution has a high decoding success rate for short-packet transmission but a lower decoding success rate in long-packet transmission. To balance the performance of rateless codes for short and long packet transmission, the Boltzmann degree distribution and the robust soliton distribution (RSD) are combined with a new joint degree distribution, called Boltzmann Robust Soliton Distribution (BRSD). Simulation results show that compared with RSD and Poisson robust soliton distribution (PRSD), the proposed joint distribution can achieve a higher decoding success rate and reduce the average degree, especially in short-packet transmission of industrial communication.

关键词： Codes Simulation Industrial communication Symbols Solitons Transforms Robustness Decoding complexity theory Physics

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Air Pollution Monitoring By Integrating Local and Global information in Self-Adaptive Multiscale Transform Domain

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IEEE Transactions on Multimedia 2025年

作者： Gu, Ke Liu, Yuchen Liu, Hongyan Liu, Bo Qiao, Junfei Lin, Weisi Zhang, Wenjun Beijing University of Technology School of Information Science and Technology Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Massey University School of Mathematical and Computational Sciences New Zealand Nanyang Technological University College of Computing and Data Science Singapore Shanghai Jiao Tong University Institute of Image Communication and Information Processing Shanghai China

As the deadliest form of pollution, air pollution had a prolonged severe damage to the human health and life safety of nearly 99% of the world's population. Facing to the problem that billions of tons of pollutants discharged into the air per year by industrial activities, this paper proposed a novel image-based air pollution monitor (IAPM) by incorporating local and global information in the self-adaptive multiscale transform domain, so as to achieve the timely and effective leakage detection of typical air pollutants from a single image. To be specific, this paper first developed a screen-shaped module according to two significant findings in visual neuroscience, which include the high sensitivity of human eyes to horizontal and vertical stimuli and the center-surround inhibition, by designing and fusing the square module, horizontal strip module and vertical strip module parallelly for simulating the behaviour of human eyes to extract local features. Second, the learnable weights and proportional mapping were applied to incorporate the screen-shaped module and lightweight vision transformer as backbone, towards more richly exploiting and fusing local and global information just as the way a brain perceives external stimuli. Third, a new self-adaptive multiscale transform domain method was devised based on two motivations from the visual characteristics of multiscale perception and the brain characteristics of self-adaptive domain transform to modify the backbone by using the operations of pooling and pointwise convolution. Extensive experiments implemented on the datasets of carbon particulate matters and ethylene leakage confirmed the superior monitoring performance of the proposed IAPM model beyond the state-of-the-art (SOTA) peers by an accuracy gain of about 4%. Furthermore, the proposed IAPM model only required 0.089 GFLOPs and 0.15 million model parameters, remarkably outperforming SOTA competitors in computational efficiency and storage resources. © 1999-2

关键词： information leakage

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Integrated Power and Hydrogen Trading in Multimicrogrid Coupled with Offsite Hydrogen Refueling Stations

Integrated Power and Hydrogen Trading in Multimicrogrid Coup...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Longyan Li Chao Ning Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

This paper proposes a novel two-level electricity and hydrogen market framework for multi-microgrids (MMGs) coupled with offsite hydrogen refueling stations (HRSs), aiming to strengthen the synergy between electricity and hydrogen. The local hydrogen market among the MMG and HRSs is modeled by multi-leader multi-follower Stackelberg game theory, in which microgrids play the role of leaders to adjust hydrogen prices while HRSs participate as followers to determine their hydrogen purchase scheme. Moreover, to deal with economic and technical issues of the MMG in a holistic manner, Nash bargaining theory is used to model the electricity transaction among microgrids. A distributed algorithm is developed to solve such games, thus reducing the cost of information communication and the risk of privacy exposure. The case study demonstrates that this market mechanism guarantees benefits for all parties and boosts the independence of MMGs by reducing transactions with the main grid.

关键词： Privacy Renewable energy sources Uncertainty Costs Hydrogen Microgrids system integration

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control Strategy of Multi-axis Serial Manipulator Based on Improved Active Disturbance Rejection control

Control Strategy of Multi-axis Serial Manipulator Based on I...

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Chinese control and Decision Conference, CCDC

作者： Pengcheng Hu Chaochen Gu Kaijie Wu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665478977

Aiming at the sudden change of load torque and uncertain external disturbance that multi-axis serial manipulators may face during operation, an improved Active Disturbance Rejection controller (ADRC) assisted by a Nonlinear Disturbance Observer (NLDOB) is designed and implemented in this paper. ADRC realizes the estimation and compensation of known model parameter perturbation, and NLDOB is introduced to estimate and compensate the load torque and other unmodeled dynamic factors of the manipulator. Meanwhile, the lumped control object model of three-bar mechanism and permanent magnet DC motor is established, and the control response curves of improved ADRC, traditional ADRC, and PID under the same conditions are compared and analyzed through simulation. The experimental results show that compared with the traditional ADRC and PID, the improved ADRC has faster response speed, smaller overshoot and stronger robustness.

关键词： Robust control Analytical models Torque Perturbation methods Simulation Estimation DC motors

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Simulation and analysis of far-field single-photon response model in Geiger avalanche mode 7

Simulation and analysis of far-field single-photon response ...

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7th Global intelligent Industry Conference, GIIC 2024

作者： Ou, Hengchang Ma, Le Jiang, Peng Wang, Pengfei Lu, Jie Zhou, Xin Sun, Jianfeng National Key Laboratory of Laser Spatial Information Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Institute of Remote Sensing Beijing100854 China 44th Research Institute China Electronics Technology Group Corporation Chongqing400060 China Research Center for Space Optical Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Zhengzhou Henan450046 China

ISBN: (纸本)9781510682986

Poisson distribution model is the basis of data analysis for GM-APD lidar, but it is only applicable to the mirror reflected target under ideal conditions, and cannot accurately describe the photon triggering process of actual GM-APD lidar detection. For the actual target with rough surface, the negative binomial distribution with M as the parameter can describe the photon distribution model more accurately. In order to solve this problem, this paper compares and analyzes Poisson distribution triggering model and the negative binomial distribution triggering model that conforms to the triggering situation of the echo signal of the target with rough surface, considering the differences in the triggering probability under different noise and signal levels. The results show that the trigger probability curve corresponding to the trigger model based on negative binomial distribution is lower in peak value, wider in bottom value and fatter overall than that of the trigger model based on Poisson distribution, and the difference between the two is more prominent under the conditions of low noise level and high signal level. This study has guiding significance for the signal extraction research based on different surface echoes. © 2024 SPIE.

关键词： Photons

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High-Resolution representation object pose estimation from monocular images

High-Resolution representation object pose estimation from m...

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2021 China Automation Congress, CAC 2021

作者： Guan, Qi Li, Wenfa Xue, Shibei Li, Dewei Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665426473

This paper addresses the 6D challenge of monocular 6D pose estimation on small targets and weak texture objects. We propose a monocular object pose estimation algorithm, High Resolution Object Pose Estimation (HRPE) based on the high-resolution feature representation, which detects the 2D keypoints and uses the Perspective-n-Point (PnP) algorithm to compute the 6D pose. HRPE can maintain high-resolution feature representation through parallel convolution of multi-resolution feature branches and repeated cross-scale fusion, generating more precise pose estimation. Experimental results show that HRPE surpasses the existing state-of-the-arts, and achieves a significant accuracy improvement for small objects, which demonstrates the effectiveness of high-resolution feature representation on pose estimation. © 2021 IEEE

关键词： Textures

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LSDNet: Boosting change detection of high-resolution remote sensing images by combining convolution-involution and ensemble coordinate attention 11

LSDNet: Boosting change detection of high-resolution remote ...

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2021 11th International Workshop on Computer Science and Engineering, WCSE 2021

作者： Liu, Yifan Liu, Jingdong Raza, Asif Li, Zeng Huo, Hong Fang, Tao Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9789811817915

Change detection has always been a crucial task in remote sensing fields, and there have already been great efforts made on it for decades. However, as high resolution (HR) remote sensing images generally contain abundant ground details, it still faces a huge challenge for their change detection, especially from the aspects of change detection accuracy and speed. Concerning this issue, a novel lightweight Siamese deep network (LSDNet) is proposed, and it combines Convolution-Involution Module (CIM) and Ensemble Coordinate Attention Module (ECAM) for boosting the change detection of HR remote sensing images. CIM summarizes the context of ground objects and reweights the importance of different positions, while ECAM aggregates multiple levels of semantic features and pays different attention to different spatial information. The experiments on CNZ data set have shown that the proposed LSDNet performs better than state-of-the-art (SOTA) change detection methods, especially it improves the accuracy by 1.92% and reduces the amount of model parameters by 32.89% compared to SNUNet-CD which has the best performance currently. © 2021 11th International Workshop on Computer Science and Engineering, WCSE 2021. All Rights Reserved.

关键词： Change detection

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