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43rd Chinese control Conference, CCC 2024

作者： Zhang, Xuanming Zeng, Xianlin Peng, Zhihong Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing100081 China

ISBN: (纸本)9789887581581

Autonomous vehicle motion planning in competitive scenarios, such as car racing, presents significant challenges due to the unpredictability of adversaries' behaviors. To generate intelligent autonomous behavior, vehicles must anticipate and react to the maneuvers of other vehicles. However, existing game-theoretic motion planning approaches often assume full knowledge of opponents' behavior patterns, overlooking the inherent uncertainty of such behaviors. This assumption can lead to suboptimal performance in critical maneuvers, such as blocking and overtaking. To address this issue, this paper proposes a motion planning method based on cognitive hierarchy theory. This method enhances the understanding of agent behavior patterns through a probabilistic model that updates inferences about each opponent's cognitive level from interaction feedback. Additionally, the proposed planner incorporates a new cost function and discrete-time control barrier functions to ensure safety during competition. The effectiveness of our planner is demonstrated through comparative simulations with the sensitivity-enhanced best response iteration (SE-IBR) algorithm. The results indicate that the proposed algorithm outperforms the SE-IBR in blocking and overtaking scenarios, highlighting its potential to improve autonomous strategies in competitive driving situations. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Cost functions

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Predicting Strategy of Rational Evader in Cooperative Pursuit: A Distributed Bimatrix Zero-sum Game Approach 43

Predicting Strategy of Rational Evader in Cooperative Pursui...

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43rd Chinese control Conference, CCC 2024

作者： Li, Yixuan Hou, Jie Zeng, Xianlin Peng, Zhihong Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing100081 China

ISBN: (纸本)9789887581581

Cooperative pursuit problems involve multiple pursuers cooperatively capturing an evader with a faster speed in an unbounded two-dimensional domain. To generate autonomous intelligent behaviors, pursuers must consider the responsive actions of the evader. Predicting the strategy of an evader often relies on the assumption that pursuers know full information, which is unrealistic. This paper proposes a strategy prediction method of multiple pursuers cooperating to predict a rational evader's strategy in a distributed game-theoretic framework. In this setup, each pursuer can only communicate with its neighbors and observe the evader's position, making the strategy prediction challenging. To tackle this issue, we model the strategy prediction problem as a bimatrix zero-sum game. Then, we propose a distributed Nash equilibrium seeking algorithm for such a game by combining the consensus averaging, the gradient tracking, and the Frank-Wolfe techniques. Furthermore, we integrate the strategy prediction into an existing cooperative pursuit method. Numerical simulations demonstrate that our method significantly improves the probability of successful capture compared to a state-of-the-art pursuit method. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Nash equilibrium

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Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 463-470页

作者：朱江辉叶航航姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System Ministry of EducationShanghai 200240China Huawei Technologies Co. Ltd.Shanghai 201206China

Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

关键词： traveling salesman problem(TSP) self-organizing mapping(SOM) combinatorial optimization neu-ral network

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Swarm-Based Dynamic Coverage of Multi-ASV Systems in the Presence of Measurement Noises

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 7237-7250页

作者： Liu, Lu Jiao, Shijian Han, Bing Li, Tieshan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China Shanghai Ship and Shipping Research Institute National Engineering Research Center of Ship & Shipping Control System Shanghai200135 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper is concerned with the dynamic coverage of multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles, limited communication distance, and measurement noises. A modular control method including planning, guidance, and control is proposed. At the planning level, a swarm-based dynamic coverage strategy is developed to achieve the coverage of a given domain. Both the collision avoidance and connectivity preservation issues are solved by using artificial potential fields. At the kinematic level, novel adaptive line-of-sight guidance laws are presented based on cascade extended state observers (CESOs), such that accurate guidance signals are given by compensating for time-varying sideslip angle and suppressing measurement noises. At the kinetic level, two CESOs are developed to estimate the internal model uncertainties and external environmental disturbance, and antidisturbance kinetic control laws are designed subsequently. The proposed CESOs overcome the noises sensitivity problem of classical observers, and thus facilitate the practical implementation under measurement noises. The input-to-state stability of the closed-loop system is confirmed by the Lyapunov theory and cascade stability theory. Simulation and hardware-in-the-loop experiment results are provided to demonstrate the effectiveness of the proposed swarm-based dynamic coverage method. © 1967-2012 IEEE.

关键词： Velocity measurement

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Study on the interactive deformation of bone needles and circum-pelvic soft tissue

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High Technology Letters 2024年第3期30卷 297-303页

作者： ZHANG Famin LEI Jingtao School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444P.R.China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai 200444 P.R.China

During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic *** this paper,a layered rig-id-flexible coupling model is proposed,and the needle-tissue interactive deformation under the load-ing is analyzed by the Rayleigh-Ritz method,in accordance with the principle of minimum potential *** pelvic musculoskeletal tissue is reversely reconstructed,and the structure of the bone is segmented into cancellous bone and cortical *** Mooney-Rivlin five-parameter hyperelastic model is used to simulate muscle,and the Ogden hyperelastic model is used to simulate adipose *** element simulation is performed by loading different magnitudes of *** accuracy of the rigid-flexible coupling model is 0.432 mm,which indicates the correctness of the needle-tis-sue interactive deformation theory analysis.

关键词： pelvic fracture reduction rigid-flexible coupling needle-tissue interactive de-formation

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A review of vehicle detection methods based on computer vision

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Journal of intelligent and Connected Vehicles 2024年第1期7卷 1-18页

作者： Changxi Ma Fansong Xue School of Traffic and Transportation Lanzhou Jiaotong UniversityLanzhou 730070China Key Laboratory of Railway Industry on Plateau Railway Transportation Intelligent Management and Control Lanzhou 730070China

With the increasing number of vehicles,there has been an unprecedented pressure on the operation and maintenance of intelligent transportation systems and transportation *** order to achieve faster and more accurate identification of traffic vehicles,computer vision and deep learning technology play a vital role and have made significant *** study summarizes the current research status,latest findings,and future development trends of traditional detection algorithms and deep learning-based detection *** the detection algorithms based on deep learning,this study focuses on the representative convolutional neural network ***,it examines the two-stage and one-stage detection algorithms,which have been extensively utilized in the field of intelligent transportation *** to traditional detection algorithms,deep learning-based detection algorithms can achieve higher accuracy and *** single-stage detection algorithm is more efficient for real-time detection,while the two-stage detection algorithm is more accurate than the single-stage detection *** the follow-up research,it is important to consider the balance between detection efficiency and detection ***,vehicle missed detection and false detection in complex scenes,such as bad weather and vehicle overlap,should be taken into *** will ensure better application of the research findings in engineering practice.

关键词： intelligent transportation system computer vision deep learning vehicle detection object detection algorithm

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Self-calibrated stacked hourglass for human pose estimation 5

Self-calibrated stacked hourglass for human pose estimation

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5th International Conference on Frontiers Technology of Information and Computer, ICFTIC 2023

作者： Tang, Tiannan Tan, Guangxing Yi, Tong Guangxi University of Science and Technology Liuzhou Key Laboratory of Intelligent Sensing and Control College of Automation Liuzhou China

ISBN: (纸本)9798350309034

In recent years, with the rapid development of deep learning algorithms such as CNN and RNN, human key point detection has been paid more and more attention. Human key point detection is always a research difficulty in computer vision because it is easily affected by complex joint occlusion, body deformation or lighting environment changes. With the proposed stacked hourglass network, it has become the mainstream method in the field of key point detection in recent years because of its repeatable upsampling and downsampling, and the addition of intermediate supervision model. Based on the stacked hourglass network, this paper introduces the self-calibrated convolutional network in SCNet network and optimates the structure of the original stacked hourglass network, and proposes a new human key point detection method named Self-calibrated stacked hourglass (SCHNs). This method effectively reduces the problem of inaccurate local feature description in the existing stacked hourglass network, and weakens the interference of useless signals in the global information to local information. Our method is trained and tested on the MPII human pose estimation dataset, and the case studys on the MSCOCO dataset. its detection results can effectively solve the problems existing in the existing stacked hourglass network, and it is significantly improved compared with other network models. © 2023 IEEE.

关键词： human keypoints detection self-calibrating convolution Stacked hourglass networks

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Long Duration Coverage control of Multiple Robotic Surface Vehicles Under Battery Energy Constraints

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1695-1698页

作者： Shengnan Gao Zhouhua Peng Haoliang Wang Lu Liu Dan Wang the School of Electrical and Control Engineering North China University of TechnologyBeijing 100144 the School of Marine Electrical Engineering Dalian Maritime UniversityDalian 116026China State Key Laboratory of Maritime Technology and Safety Dalian 116026 Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian 116026 the School of Marine Engineering Dalian Maritime UniversityDalian 116026

Dear Editor,This letter addresses long duration coverage problem of multiple robotic surface vehicles(RSVs) subject to battery energy constraints,in addition to uncertainties and disturbances. An anti-disturbance energy-aware control method is proposed for performing coverage task of RSVs. Firstly, a centroidal Voronoi tessellation(CVT) is used to optimize the partition of the given coverage area.

关键词： Robotic Battery partition

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An Amalgamated CNN-Transformer Network for Lightweight Image Super-Resolution

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第3期9卷 1376-1387页

作者： Fang, Jinsheng Lin, Hanjiang Zeng, Kun School of Computer Science and Engineering Minnan Normal University Zhangzhou363000 China Key Laboratory of Data Science and Intelligence Application Fujian Province University Fujian Zhangzhou363000 China School of Computer and Control engineering Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

Recently, Transformer-based methods for single image super-resolution (SISR) have achieved better performance advantages than the methods based on convolutional neural network (CNN). Exploiting self-attention mechanism to model global context definitely improves the SR results. However, the neglect of local information will bring inevitable reduction of the network performance. In this work, we propose an Amalgamated CNN-Transformer network for lightweight SR, namely ACTSR. Specifically, an amalgamated CNN-Transformer block (ACTB) is developed to extract the useful information of both local and global features. By employing stacked ACTBs, our ACTSR extracts more informative deep features beneficially for super-resolution reconstruction to improve network performance while keeps lightweight and flexible enough. Extensive experiments on commonly used benchmark datasets validate our ACTSR outperforms the advanced competitors. Our codes are available at: https://***/ginsengf/ACTSR. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Convolutional neural networks

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Distributed control of Vehicle Platoon With Input Saturation Under DoS Attacks

Distributed Control of Vehicle Platoon With Input Saturation...

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2024 China automation Congress, CAC 2024

作者： Gong, Jionghao Huang, Longwang Li, Yongfu Key Laboratory of Intelligent Air-ground Cooperative Control for University in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9798350368604

This paper focuses on the control of connected vehicle platoon when subjected to random Denial-of-Service (DoS) attacks. Firstly, to better describe the impact of a random DoS attack, the attack is modeled as a random communication topology switching process using a stochastic Markov process. Then, to cope with the DoS attack, a security control law considering the dynamic coupling between vehicles and the input saturation property is proposed on the basis of the recovery mechanism. After that, the relevant parameters of the proposed controller are calculated by solving the linear matrix inequality (LMI), while the Lyapunov- Razumikhin theory is applied to establish a sufficient condition for the stabilization of the platooning system under DoS attack. Finally, the performance of the proposed control protocol is confirmed by the numerical simulation of a vehicular platoon system containing one leader vehicle and six follower vehicles. © 2024 IEEE.

关键词： Markov processes

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