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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

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Consensus of Second-order Matrix-weighted Multi-agent Networks 16

Consensus of Second-order Matrix-weighted Multi-agent Networ...

引用

16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Wang, Chongzhi Pan, Lulu Li, Dewei Shao, Haibin Xi, Yugeng Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Minist Educ China Shanghai 200240 Peoples R China

ISBN: (纸本)9781728177090

this paper investigates consensus problem of second-order multi-agent system on matrix-weighted networks. It is shown that when the null space of the Gauge transformed graph Laplacian is spanned by the Kronecker product of an all-one vector and a set of orthogonal vectors, the algebraic multiplicity of eigenvalue zero cannot exceed the nullity of the graph Laplacian, thus admitting a proper blocking of the system matrix's Jordan normal form. Second-order bipartite consensus is thereby achieved independent of the structural balance of the network. Simulation examples are provided to demonstrate the theoretical results.

关键词： Matrix-weighted networks bipartite consensus second-order multi-agent system structural balance

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Mean Field LQ Games with a Finite Number of Agents 16

Mean Field LQ Games with a Finite Number of Agents

引用

16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Wang, Bing-Chang Zhang, Huanshui Fu, Minyue Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao Peoples R China Univ Newcastle Sch Elect Engn & Comp Sci Newcastle NSW Australia

ISBN: (纸本)9781728177090

In this paper, we are concerned with a new class of mean field games which involve a finite number of agents. With help of conditional mathematical expectation, we obtain necessary and sufficient conditions for the existence of the decentralized open-loop Nash equilibrium for finite-population games. By decoupling a non-standard forward-backward stochastic differential equation, we design a set of decentralized strategies in term of two differential Riccati equations. Instead of the epsilon-Nash equilibrium, the set of decentralized strategies is shown be a Nash equilibrium. Furthermore, we examine the infinite-horizon problem and give a neat condition for solvability of the related algebraic Riccati equation.

关键词： Game theory

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Real-Time Queue Length Estimation With Trajectory Reconstruction Using Surveillance Data 16

Real-Time Queue Length Estimation With Trajectory Reconstruc...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Sheng, Zihao Xue, Shibei Xu, Yunwen Li, Dewei Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9781728177090

this paper presents a new method to estimate real-time queue lengths at a signalized intersection by utilizing limited data extracted from surveillance videos. this method focuses on reconstructing vehicles' trajectories on an entire road segment. the real-time queue length can be derived from these reconstructed trajectories. In order to improve the accuracy of the trajectory reconstruction, a built-up car-following model is proposed to reconstruct the trajectories of vehicles joining and leaving the queue, respectively, which are further corrected by a fusion algorithm. the proposed method was validated in the Next Generation Simulation dataset, and the queue length for each signal cycle can be estimated with a high accuracy. the results show that the proposed method has a higher precision compared to three baseline models.

关键词： Trajectories

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Towards Semantic Scene Segmentation for Autonomous Agricultural Vehicles 16

Towards Semantic Scene Segmentation for Autonomous Agricultu...

引用

16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Mujkic, Esma Hermann, Dan Ravn, Ole Bilde, Morten L. Andersen, Nils A. Tech Univ Denmark Dept Elect Engn Automat & Control Grp Lyngby Denmark AGCO AS Res & Adv Engn Randers Denmark

ISBN: (纸本)9781728177090

the development of autonomous agricultural vehicles depends on accurate visual interpretation of the environment. Semantic pixel-wise segmentation plays an important role in achieving a more detailed description of the scene and understanding of the spatial-relationship between different objects. In this paper, a deep architecture for road scene and indoor scene segmentation, SegNet, is applied in solving the scene recognition problem for the agricultural environment. the network is trained on an agriculture image dataset collected during field operation. the problem focuses on the segmentation of five classes of structures commonly found in the fields: vegetation, grass, ground, crop field and obstacles. We apply frequency balancing to address the challenge of class imbalance and transfer learning technique. the quantitative performance of the network is evaluated using pixel accuracy and intersection over union metrics. Moreover, we present an approach for an infield qualitative validation of the trained network.

关键词： Pixels

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Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation 18

Self-supervised Monocular Depth Estimation for All Day Image...

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18th IEEE/CVF international conference on Computer vision (ICCV)

作者： Liu, Lina Song, Xibin Wang, Mengmeng Liu, Yong Zhang, Liangjun Zhejiang Univ Inst Cyber Syst & Control Hangzhou Peoples R China Baidu Res Beijing Peoples R China Zhejiang Univ Huzhou Inst Hangzhou Peoples R China Natl Engn Lab Deep Learning Technol & Applicat Beijing Peoples R China

ISBN: (纸本)9781665428125

Remarkable results have been achieved by DCNN based self-supervised depth estimation approaches. However, most of these approaches can only handle either day-time or night-time images, while their performance degrades for all-day images due to large domain shift and the variation of illumination between day and night images. To relieve these limitations, we propose a domain-separated network for self-supervised depth estimation of all-day images. Specifically, to relieve the negative influence of disturbing terms (illumination, etc.), we partition the information of day and night image pairs into two complementary sub-spaces: private and invariant domains, where the former contains the unique information (illumination, etc.) of day and night images and the latter contains essential shared information (texture, etc.). Meanwhile, to guarantee that the day and night images contain the same information, the domain-separated network takes the day-time images and corresponding night-time images (generated by GAN) as input, and the private and invariant feature extractors are learned by orthogonality and similarity loss, where the domain gap can be alleviated, thus better depth maps can be expected. Meanwhile, the reconstruction and photometric losses are utilized to estimate complementary information and depth maps effectively. Experimental results demonstrate that our approach achieves state-of-the-art depth estimation results for all-day images on the challenging Oxford RobotCar dataset, proving the superiority of our proposed approach. Code and data split are available at https://***/LINA-lln/ADDS-DepthNet.

关键词： Textures

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Model Predictive control Based On Spider monkey optimization Algorithm of Interleaved Parallel Bidirectional DC-DC Converter 16

Model Predictive Control Based On Spider monkey optimization...

引用

16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Lan, Yueyang Chen, Qihong Zhang, Liyan Long, Rong Wuhan Univ Technol Sch Automat Wuhan Peoples R China Huazhong Agr Univ Wuhan Peoples R China

ISBN: (纸本)9781728177090

Taking the high real-time performance, good stability and high reliability of DC-DC converter in electric vehicles as the research target, a constrained model predictive control (MPC) based on spider monkey optimization algorithm was proposed. Taking the Buck mode for an example, the equivalent circuit model is obtained under different switching states, and the state space model is established, then the prediction model is established through discretization. Define the appropriate cost function according to the control requirements and add the constraints of the control variables. the spider monkey optimization algorithm(SMO) is introduced to solve optimization problem of the constrained MPC in order to get the optimal solution more quickly and accurately. the simulation was carried out by MATLAB/Simulink, and the simulation results of PI control, MPC based on Particle Swarm Optimization(PSO-MPC) and SMO-MPC was compared. the simulation show that the converter using MPC has better control effect, and SMO is feasible and effective.

关键词： DC-DC converters Model predictive control PI control spider monkey optimization algorithm

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Hand-Eye Calibration of Surgical Robots Based on a BP Neural Network Optimized by Using an Improved Sparrow Search Algorithm

Hand-Eye Calibration of Surgical Robots Based on a BP Neural...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jiaqi Zhu Weibo Ning Ye Yuan Hongjiang Chen Weijun Zhou Yecheng Tan Shuxing He Jun Hu Zhun Fan Shantou University Shantou China Hospital of Medical College of Shantou University Shantou China

ISBN: (纸本)9781665476881

Hand-eye calibration methods for surgical robots are employed to derive a transformation between the robot's base motor and visual coordinate systems. Accurately completing hand-eye calibration procedures provides an important guarantee that a surgical robot will exhibit positioning and execution accuracy sufficient for assisting surgeons in successfully completing surgical procedures. To improve the accuracy of robot hand-eye calibration methods based on backpropagation neural network (BPNN) models, we propose a modified BP neural network optimized using the sparrow search algorithm for hand-eye calibration model (TSSABPNN), which can enhance population initialization by applying tent mapping. Furthermore, we also design a new sliding 3D calibration tool. the sparrow search algorithm exhibits good local exploration ability, and we introduce a tent map with ergodic characteristics to initialize the sparrow population information, which further improves the network's global search ability and convergence rate. Finally, we experimentally analyze four calibration models: TSSABP NN model, a BP NN model optimized using a genetic algorithm of simulated annealing (GASABPNN), an unoptimized BP NN model, and the traditional singular value decomposition method. the results indicate that the proposed TSSABP NN model exhibits the maximum calibration precision and best robustness and iteratively converges faster.

关键词： Analytical models Medical robotics three-dimensional displays Robot kinematics Sociology Artificial neural networks Robustness

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Feasible Schedule Under Faults in the Assembly System 16

Feasible Schedule Under Faults in The Assembly System

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Majdzik, Pawel Univ Zielona Gora Inst Control & Computat Engn Zielona Gora Poland

ISBN: (纸本)9781728177090

this paper addresses an application of a fault-tolerant control to a cubes ' packing system. the core issue concerns a control of a set of parallel manipulators which transport cubes from various points to a final storage. the main contribution of this paper is an analytical description of a set of manipulators by means of the max-plus algebra equations. the task of these manipulators is a handling of transport of cubes in accordance with a reference schedule. the proposed mathematical approach has to take into consideration both synchronization and choice issues as well as faults. In addition, diagnostics and fault-tolerant control strategy are developed and applied to the system of cubes' packing being considered. All constraints are defined and incorporated into this control strategy. the proposed approach is able to compensate or eliminate the influence of some faults, e.g., delays occurring in the manipulators or reduced velocities of transportation means. Finally, an example exhibiting effectiveness of the proposed control scheme is presented.

关键词： flexible manufacturing system max-plus algebra fault-tolerant control discrete event dynamic system

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Robust Adaptive Fault-Tolerant Coordinated control for Biaxial Gantry System with Friction Compensation 16

Robust Adaptive Fault-Tolerant Coordinated Control for Biaxi...

引用

16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Wang, Kangjun Liu, Xiangbin Su, Hongye Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Zhejiang Univ Inst Cyber Syst & Control Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9781728177090

In this paper, a novel robust adaptive fault-tolerant coordinated control is proposed for the contour tracking problem of unknown biaxial linear-motor-driven gantry system subject to time-varying actuator faults. Firstly, the dynamic model of the contour error is established by coordinate transformation. the time-varying actuator faults including loss of effectiveness and bias faults with unknown failure time are considered in controller design. the robust adaption law with smooth projection modification is developed to handle for the effect of parametric uncertainties on the system. the proposed control scheme can guarantee that all the signals in the closed-loop system are ultimately bounded even if time-varying actuator faults of the gantry system occur. Finally, two numerical simulations are conducted to show the effectiveness of the proposed control method.

关键词： Biaxial Gantry Coordinated control Actuator Fault Robust Adaptive control Continuous Friction Compensation

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Assessment of an Effective Range of Detecting Intruder Aerial Drone Using Onboard EO-Sensor 6

Assessment of an Effective Range of Detecting Intruder Aeria...

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6th international conference on control, automation and robotics (ICCAR)

作者： Hao, Tan Kang Yakimenko, Oleg Naval Postgrad Sch Dept Syst Engn Monterey CA 93943 USA

ISBN: (纸本)9781728161396

this paper discusses the results of experiments on using an electro-optical (EO) sensor to detect an aerial intruder based on a small unmanned aerial system (sUAS) and assess its intentions. When matured, this technology can be used for enabling vision-based situational awareness and mid-air collision avoidance when operating in a cluttered environment, as well as for counter-UAS operations. the paper starts with a discussion of a theoretical capability of vision-based sUAS detection using an EO sensor onboard a drone, followed the outline of a simple drone detection algorithm. It then proceeds with reviewing a series of field experiments conducted to assess the algorithm's operational effectiveness. the tests results demonstrate the viability of the proposed approach, thus suggesting further exploration.

关键词： unmanned aerial system (UAS) counter-UAS electro-optical sensor computer vision range and movement detection

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