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arXiv 2024年

作者： Hu, Xuemin Chen, Pan Wen, Yijun Tang, Bo Chen, Long School of Artificial Intelligence Hubei University Wuhan430062 China Key Laboratory of Intelligent Sensing System and Security Hubei University Ministry of Education Hubei Wuhan430062 China Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States State Key Laboratory of Multimodal Artificial Intelligence Systems State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an710049 China

Reinforcement learning (RL) has been widely used in decision-making and control tasks, but the risk is very high for the agent in the training process due to the requirements of interaction with the environment, which seriously limits its industrial applications such as autonomous driving systems. Safe RL methods are developed to handle this issue by constraining the expected safety violation costs as a training objective, but the occurring probability of an unsafe state is still high, which is unacceptable in autonomous driving tasks. Moreover, these methods are difficult to achieve a balance between the cost and return expectations, which leads to learning performance degradation for the algorithms. In this paper, we propose a novel algorithm based on the long and short-term constraints (LSTC) for safe RL. The short-term constraint aims to enhance the shortterm state safety that the vehicle explores, while the long-term constraint enhances the overall safety of the vehicle throughout the decision-making process, both of which are jointly used to enhance the vehicle safety in the training process. In addition, we develop a safe RL method with dual-constraint optimization based on the Lagrange multiplier to optimize the training process for end-to-end autonomous driving. Comprehensive experiments were conducted on the MetaDrive simulator. Experimental results demonstrate that the proposed method achieves higher safety in continuous state and action tasks, and exhibits higher exploration performance in long-distance decision-making tasks compared with state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Improved Interpolation with Sub-Pixel Relocation Method for Strong Barrel Distortion

SSRN

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SSRN 2022年

作者： Yuwen, Xuan Zhang, Silong Chen, Long Zhang, Hui School of Transportation Science and Engineering Beihang University Beijing102206 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

In this paper, we propose an improved interpolation method with sub-pixel relocation method to correct fisheye images with strong barrel distortion. The proposed method takes as inputs the fisheye image and the projection model, and outputs the corrected perspective image. In the method, we project the fisheye image pixels to perspective image plane using the backward projection. The projected pixels are treated as scatter data and their location is refined by the sub-pixel relocation method. The method is designed to aim at the subpixel bias phenomenon of the projected *** sub-pixel relocation method relocates the projected pixel centers to the centers of the projected pixels. Then the relocated points are meshed by the Voronoi diagram method to select the neighbors of the interpolation points. The weights of the neighbors are calculated using the inverse distance method. The index of the neighbor and their weights are stored in a look-up-table structure for reutilization. For each fisheye image, the proposed method can quickly find the neighbors of the interpolation points and the weight of each neighbor through the look-up-table. Test results illustrate that the proposed method achieves the best accuracy among the tested method for fisheye images with strong barrel distortion. © 2022, The Authors. All rights reserved.

关键词： Interpolation

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Novel sliding-mode disturbance observer-based tracking control with applications to robot manipulators

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Science China(Information Sciences) 2021年第7期64卷 80-91页

作者： Tairen SUN Long CHENG Zengguang HOU Min TAN School of Electrical and Information Engineering Jiangsu University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

This paper proposes a sliding-mode disturbance observer(SMDOB)-based tracking controller for a class of nonlinear systems with modeling uncertainties and external disturbances. The SMDOB is constructed using an extended state observer embedded by a filtered sliding mode term. The chattering caused by the sliding mode is compressed by the frequency bandwidths of both the extended state observer and the control system. The novelties of the proposed controller are as follows:(1) The semiglobal asymptotical stability of the combined controller-observer system is guaranteed without the boundedness assumption of the time derivatives of modeling uncertainties;(2) the SMDOB can be implemented with a low complexity because of only three parameters to be tuned. Applications to robot manipulators illustrate the effectiveness of the SMDOB-based tracking control strategy.

关键词： adaptive control robot manipulator disturbance observer sliding mode

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Accelerating Realistic Multi-Route Traffic Flow Generation Based on Improved Simulated Annealing Algorithms

Accelerating Realistic Multi-Route Traffic Flow Generation B...

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International Conference on Intelligent Transportation

作者： Hongrui Chen Yan Zhang Xingyuan Dai Jiaming Sun Fei Cong Yanan Lu Bingji Xu Yisheng Lv School of Information Engineering China University of Geosciences (Beijing) Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China China Telecom Digital City Technology Co. Ltd Hebei China

In the traffic simulation system, the data quality and inference speed of traffic flow generation have a direct impact on the correlation between analysis results and actual traffic conditions, as well as the efficiency of utilization. Existing traffic flow generation methods often rely on abundant sensor data and involve time-consuming generation processes. To reduce time costs, in this paper, we propose an efficient Multi-Route Traffic Flow Generator (MTFG). The generation process is divided into two parts: multi-route generation and route quantity search. In the multi-route generation, we employ a Multi-Route Generator (MRG) methodology leveraging topological road network data to generate distinct traffic routes for identical origin-destination pairs. This ensures the attainment of diversified vehicle trajectories even within a sparsely equipped detector network. Subsequently, in the route quantity search, we employ an improved simulated annealing algorithm to systematically explore the traffic route quantity based on the generated multiple routes, thereby significantly amplifying the algorithm's efficacy in route generation. We validate the effectiveness of MTFG using the Malaga open dataset on the SUMO simulation platform. Compared to the strong baseline Flow Generator Algorithm (FGA) with a training time exceeding 2.5h, MTFG achieves the target metric in just 1h under the same conditions, saving over 55% of training time.

关键词：

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A Preliminary Study on the Functional Coupling between Nerve and Blood Microcirculation for Applications in Rehabilitation Robots

A Preliminary Study on the Functional Coupling between Nerve...

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IEEE International Conference on Robotics and Biomimetics

作者： Qingge Li Yuanzhe Dong Yuxiang Zhang Xin Wang Naifu Jiang Jianping Huang Han Cui Lan Tian Yue Zheng Xiangxin Li Lin Wang Guanglin Li Wenyuan Liang Liang Peng Peng Fang CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China National Research Center for Rehabilitation Technical Aids Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Rehabilitation robots play an important role in the motor function rehabilitation for stroke survivors with hemiplegia. However, the rehabilitation effect of current robots is still limited partly because a single training of motor function can be strongly affected by the decreased blood supply function of the bedridden patients. This work proposed an approach to study the coupling relationship between the motor and blood supply functions by combining the synchronously recorded EEG and cerebral blood oxygen information, where the cerebrations in different movement paradigms were analyzed from an aspect of "functional coupling". The results show that the information of oxyhemoglobin concentration change (ΔHbO) can effectively indicate the cortex activation, and a stronger blood supply is needed in cortexes to perform body movements. The correlations within motor cortexes are significantly stronger than the ones between motor and prefrontal cortexes, and a higher resistance level of extremity training will cause stronger correlations. Calculation of transfer entropy (TE) shows that there exists a bidirectional information transmission between the electrophysiological and blood supply signals, and more information is transmitted always in the direction from ΔHbO to EEG than in the opposite direction. The information transmission or the coupling relationship can be significantly enhanced by extremity movements, and large TE values are achieved in the Theta, Beta and Gamma frequency bands of EEG that correspond to motor functions. This work has demonstrated the functional coupling between nerve and blood microcirculation, which would provide a technical guidance to improve the rehabilitation effect for current robot systems and have great application potentials.

关键词：

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Muscle Synergy Analysis Based on NMF for Lower Limb Motor Function Assessment

Muscle Synergy Analysis Based on NMF for Lower Limb Motor Fu...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Xiang, Kexin Wang, Weiqun Hou, Zeng-Guang Zhang, Chutian Wang, Jiaxing Shi, Weiguo Jiao, Yuze Lin, Tianyu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The School of Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China Macau Institute of Systems Engineering Macau University of Science and Technology China The CASIAMUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665481090

Accurate rehabilitation assessments are essential for designing effective rehabilitation methods and helping patients recover better. It's well known that commonly used scale assessment methods for neurorehabilitation suffer from the issue of subjectivity, thus investigation of objective assessment methods is very necessary. Muscle synergy analysis can be uesd to assess limb motor functions from the perspective of neuromuscular control. In this paper, a method for evaluation of human lower limb motor functions based on muscle synergy analysis is presented. Muscle synergy modules are designed using surface electromyography (sEMG) signals of the subjects' lower limbs by non-negative matrix factorizations (NMF). By comparing the cosine similarities of these synergy modules, it can be seen that muscle synergies of healthy subjects and patients are significantly different, while they are similar among healthy subjects. Therefore, a reference synergy module (RSM) is designed by averaging the muscle synergy modules for healthy subjects, and the similarities can be calculated by comparing the synergy modules for healthy subjects or patients with the RSM. In the experiment carried out in this study, average similarities of the three synergy modules for healthy subjects are respectively 0.97166, 0.87368 and 0.84932, and on the other hand, the average similarities for the three synergy modules for patients are respectively 0.59979, 0.56426 and 0.69042. Therefore, the similarities for healthy subjects are much higher than those for SCI patients, which denotes that the similarity between an individual synergy module and the RSM can be used as an objective assessing index for evaluating patients' motor function. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Research on measuring magnetic field around 10kV cable based on three-split magnetic core

Research on measuring magnetic field around 10kV cable based...

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Energy, Electrical and Power Engineering (CEEPE), International Conference on

作者： Zhe Hou Sen Teng Wenqiang Dang Xiahaoyue Yun Zeli Ju Yang You Zixiong Cai Power Equipment Condition Assessment Center State Grid Shaanxi Electric Power Research Institute Xi’an China Power Distribution Network Department State Grid Shaanxi Electric Power Company Xi’an China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350375794

ISBN: (纸本)9798350375800

The utilization of 10kV cable in urban distribution networks and industrial settings necessitates regular maintenance and fault detection to guarantee uninterrupted power supply. Ensuring the de-energization of inspected cables on-site is crucial for operator safety, yet current methods for evaluating the energization status of 10kV cables lack effectiveness. This study introduces an electromagnetic detection sensor utilizing a three-split magnetic core design, aimed at addressing the issue of zero magnetic field integral resulting from the three-phase current vector sum of 0 in a 10kV cable. This study employs theoretical analysis and finite element simulation to investigate the magnetic induction state of a three-split magnetic core surrounding a 10kV distribution cable. The findings confirm that the three-split magnetic core is capable of detecting the magnetic field generated by the current load in the phase conductor on the outer surface of the 10kV cable. These results offer theoretical justification for further research into live state detection technology for 10kV cables utilizing the three-split magnetic core.

关键词： Magnetic flux density Sensitivity Power cables Magnetic cores Solids Vectors Finite element analysis

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Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways

arXiv

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arXiv 2023年

作者： Guo, Yu Liu, Ryan Wen Qu, Jingxiang Lu, Yuxu Zhu, Fenghua Lv, Yisheng The School of Navigation Wuhan University of Technology Wuhan430063 China The National Engineering Research Center for Water Transport Safety Wuhan430063 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

The automatic identification system (AIS) and video cameras have been widely exploited for vessel traffic surveillance in inland waterways. The AIS data could provide the vessel identity and dynamic information on vessel position and movements. In contrast, the video data could describe the visual appearances of moving vessels, but without knowing the information on identity, position and movements, etc. To further improve vessel traffic surveillance, it becomes necessary to fuse the AIS and video data to simultaneously capture the visual features, identity and dynamic information for the vessels of interest. However, traditional data fusion methods easily suffer from several potential limitations, e.g., asynchronous messages, missing data, random outliers, etc. In this work, we first extract the AIS- and video-based vessel trajectories, and then propose a deep learning-enabled asynchronous trajectory matching method (named DeepSORVF) to fuse the AIS-based vessel information with the corresponding visual targets. In addition, by combining the AIS- and video-based movement features, we also present a prior knowledge-driven anti-occlusion method to yield accurate and robust vessel tracking results under occlusion conditions. To validate the efficacy of our DeepSORVF, we have also constructed a new benchmark dataset (termed FVessel) for vessel detection, tracking, and data fusion. It consists of many videos and the corresponding AIS data collected in various weather conditions and locations. The experimental results have demonstrated that our method is capable of guaranteeing high-reliable data fusion and anti-occlusion vessel tracking. © 2023, CC BY.

关键词： Deep neural networks

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Path Planning of Mobile Robot Based on an Improved Genetic Algorithm 2

Path Planning of Mobile Robot Based on an Improved Genetic A...

引用

2nd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2022

作者： Chen, Zenghua Xiong, Gang Liu, Sheng Shen, Zhen Li, Yue Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Chang'an University School of Automobile Xi'an China

ISBN: (纸本)9781665492270

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations;Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm;Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles;Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning. © 2022 IEEE.

关键词： Genetic algorithms

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Hand Position Tracking based on Optimized Consistent Extended Kalman Filter

Hand Position Tracking based on Optimized Consistent Extende...

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第34届中国控制与决策会议

作者： Lin Tian Wenchao Xue Long Cheng The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences The Key Laboratory of Systems and Control National Center for Mathematics and Interdisciplinary SciencesAcademy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

This paper proposes a hand position tracking algorithm based on optimized consistent extended Kalman filter(CEKF).By introducing the previous work of the authors and analyzing the parameter of the original CEKF algorithm,the key parameter that is negatively correlated with the degree of the estimation of uncertain dynamics is ***,two metaheuristic methods,the Genetic Algorithm(GA) and the Particle Swarm Optimization(PSO) are used to optimize the original CEKF *** quantify the performance of the algorithms,the root-mean-square error(RMSE) is employed as the performance ***,the numerical simulation and practical experiment of the hand position tracking are carried out,and the optimized algorithm achieves 9.52% and 10.94% improvements of the performance,respectively.

关键词： Consistency Extended Kalman Filter Genetic Algorithm Particle Swarm Optimization

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