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Autonomous transfer robot system for commercial vehicles at Ro-Ro terminals

Expert systems with Applications 2025年 289卷

作者： Lin Zhang Yongkang Xu Jinge Si Runjiao Bao Yichen An Shoukun Wang Junzheng Wang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China

With the rapid development of smart port infrastructure, ports such as Rotterdam and Ningbo have made significant progress in automating container handling. However, traditional manual transfer methods at roll-on/roll-off (Ro-Ro) terminals can no longer meet the growing demands for low-cost, high-efficiency, and standardized operations, driven by increased port throughput, labor shortages, and operational complexity. This study introduces a novel autonomous robot transfer system comprising commercial vehicle transfer robots, a cloud scheduling system, and robotic operation systems. An electric transfer robot with independent four-wheel drive and steering was developed for heavy-duty commercial vehicle transfers, featuring a modular software architecture with cloud-based scheduling and planning, and robot perception and control modules. To support multi-robot cooperative transfer in open yard environments, we propose a task allocation algorithm based on an adaptive particle swarm genetic algorithm and an enhanced conflict-aware path planning method under kinematic constraints. For precise and safe vehicle pick-up and drop-off under complex conditions, a multi-stage fusion algorithm is introduced for vehicle body localization, orientation estimation, and wheel alignment, together with a predictive docking control algorithm using virtual transfer vehicle tracking. The system was deployed at the Ro-Ro terminal of Yantai Port, Shandong Province, China, where targeted experiments were conducted. Results demonstrate centimeter-level accuracy in vehicle handling, a transfer efficiency of 91 % compared to manual operations, and the operating time reaches 2–3 times. These findings validate the effectiveness and practical value of the proposed robot system and its key technologies.

关键词： Autonomous docking Autonomous transfer of commercial vehicles Robot system Scheduling planning Straddle-structured robots

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Multilevel filtering image denoising algorithm based on edge information fusion 16

Multilevel filtering image denoising algorithm based on edge...

引用

16th National Conference on Laser Technology and Optoelectronics

作者： Zhang, Xin Sun, Jianfeng Jiang, Peng Zhou, Xin Qiu, Changrui Zhang, Yinbo Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Industrial Technology Innovation Research Institute Co. Ltd Beijing101312 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9781510646643

ISBN: (纸本)9781510646636

Edges are critical important for the visual appearance of images. The traditional denoising algorithms are difficult to preserve the edges of the image while removing the noise of ICCD sensing image. At the same time, it is difficult to eliminate the problems of image darkness and low resolution caused by uneven illumination. This paper proposes a multilevel filtering image denoising algorithm based on edge information fusion. The target edges detection of the image after non-local means (NL-means) filtering is carried out based on the eight-direction Sobel operator. In order to filter the false edge points and residual noise, an adaptive threshold is determined according to the mean and variance of the eight neighborhood pixels of the detected pixel. Meanwhile, homomorphic filtering is used to enhance the image contrast and uniformity. By comparing the pixel values of the edge image and the homomorphic filtered image, the final denoised image is obtained by fusing the two images. The results indicate that, compared with the traditional algorithms, the edge preserving ability of the proposed algorithm is improved by more than 20%, and the denoising ability is improved by 63.5% for building target. For specific targets (vehicle), the results demonstrate that the proposed algorithm have the maximum edge preserving index and contrast, and the minimum non-uniformity. This algorithm lays a foundation for target segmentation and recognition. © 2021 SPIE.

关键词： Image fusion

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Depth imaging through realistic fog using Gm-APD Lidar 16

Depth imaging through realistic fog using Gm-APD Lidar

引用

16th National Conference on Laser Technology and Optoelectronics

作者： Zhang, Yinbo Li, Sining Jiang, Peng Sun, Jianfeng Liu, Di Yang, Xianhui Zhang, Xin Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser 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 Industrial Technology Innovation Research Institute Co. Ltd Beijing101312 China

ISBN: (数字)9781510646643

ISBN: (纸本)9781510646636

When using Gm-APD Lidar for depth imaging through realistic fog, the echo signal of the target is submerged in the background noise due to the strong absorption and scattering characteristics of the fog particles, resulting in serious defect of the recovered depth image of the target. To solve this problem, this paper proposes a dual-parameter estimation algorithm based on continuous wavelet transform (CWT) and maximum likelihood estimation (MLE) to improve the accuracy of fog signal estimation. Then the target and the fog signal are separated by estimating the fog signal of each pixel. Finally, the depth image of the separated target is processed by cross pixel complement and median filtering algorithms to improve the integrity of the target image. The experimental results show that, compared with the traditional algorithm, the target recovery of the reconstructed image is improved by 0.337, and the relative average ranging error is reduced by 0.3897. This research improves the weather adaptability of Gm-APD Lidar. © 2021 SPIE.

关键词： Optical radar

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Fractional-order Virtual Model control for Trotting Motion of Quadruped Robot

Fractional-order Virtual Model Control for Trotting Motion o...

引用

Chinese control and decision Conference, CCDC

作者： JiangBo Zhao Shicheng Ma Shanshuai Niu Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Virtual model control (VMC) is the most widely-used method for motion control of quadruped robot. VMC could decrease the abrupt ground reaction force and realize compliant interaction between foot and ground at the cost of control precision. To improve the robustness and precision of VMC, we integrate a fractional-order virtual damper with the classical VMC and propose a fractional-order VMC (FOVMC) for quadruped robot trotting motion. And we provide the implementation details about optimization-based FOVMC parameter tuning method and carry out the trotting experiments on the quadruped robot platform. The experiment results demonstrate that FOVMC could improve the precision of single-leg motion control and achieve a better whole-body trotting performance than classical VMC.

关键词： Legged locomotion Motion control Robot kinematics Foot Torque Force

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Echo state network based symbol detection in chaotic baseband wireless communication

arXiv

引用

arXiv 2021年

作者： Yin, Hui-Ping Bai, Chao Ren, Hai-Peng The Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China The Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China

In some Internet of Things (IoT) applications, multipath propagation is a main constraint of communication channel. Recently, the chaotic baseband wireless communication system (CBWCS) is promising to eliminate the inter-symbol interference (ISI) caused by multipath propagation. However, the current technique is only capable of removing the partial effect of ISI, due to only past decoded bits are available for the suboptimal decoding threshold calculation. However, the future transmitting bits also contribute to the threshold. The unavailable future information bits needed by the optimal decoding threshold are an obstacle to further improve the bit error rate (BER) performance. Different from the previous method using echo state network (ESN) to predict one future information bit, the proposed method in this paper predicts the optimal threshold directly using ESN. The proposed ESN-based threshold prediction method simplifies the symbol decoding operation by removing the threshold calculation from the transmitting symbols and channel information, which achieves better BER performance as compared to the previous method. The reason for this superior result lies in two folds, first, the proposed ESN is capable of using more future symbols information conveyed by the ESN input to get more accurate threshold;second, the proposed method here does not need to estimate the channel information using Least Square method, which avoids the extra error caused by inaccurate channel information estimation. By this way, the calculation complexity is decreased as compared to the previous method. Simulation results and experiment based on a wireless open-access research platform under a practical wireless channel, show the effectiveness and superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Bit error rate

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Design and Performance Analysis of a Chaotic Pseudo Orthogonal Carriers Multi-Access Communication system

arXiv

引用

arXiv 2021年

作者： Bai, Chao Yao, Jun-Liang Sun, Yu-Zhe Ren, Hai-Peng Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

A Chaotic Pseudo Orthogonal Carriers Multi-Access (CPOCMA) communication based on Chaotic Pseudo Orthogonal Shape-forming Filter (CPOSF) bank, Chaotic Pseudo Orthogonal Matched Filter (CPOMF) bank and Chaotic Pseudo Orthogonal Correlation Filter (CPOCF) bank is proposed in this work. At the transmitter, the multiple CPOSFs are used to generate pseudo orthogonal signals. It provides a good trade-off between spectrum efficiency and high bit transmission rate. At the receiver, the CPOMF bank and CPOCF bank are used to maximize the Signal-to-Noise Ratio (SNR) and extract the received information from each sub-channel, respectively. The received signal is demodulated by averaging the sampled sequence from the matched filter bank output and sorting the sampling sequence from the CPOCF bank output to recover the transmitted information bits. The proposed CPOCMA communication system not only offers multiuser access with high reliability and high data transmission rate, but also achieves higher spectrum efficiency. Analytical Bit Error Rate (BER) expression is derived. The proposed communication system performance has been evaluated in Additive White Gaussian Noise (AWGN) channel and wireless channel by both numerical simulations and experiments based on a Wireless open-Access Research Platform (WARP), the results show the effectiveness and the superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Numerical methods

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Data-Driven Interval Robust Optimization Method of Vpp Bidding Strategy in Spot Market Under Multiple Uncertainties

SSRN

引用

SSRN 2024年

作者： Ma, Ying Li, Zhen Liu, Ruyi Liu, Bin Yu, Samson S. Liao, Xiaozhong Shi, Peng School of Automation Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing100081 China School of Mathematics and Statistics University of Sydney NSW2006 Australia Beijing102249 China School of Engineering Deakin University VIC3216 Australia School of Electrical and Electronic Engineering Univerty of Adelaide SA5005 Australia Research and Innovation Center Obuda University Budapest1034 Hungary

Virtual power plant (VPP) participating in the spot market can improve the flexibility of new-type power systems with the increasing penetration of renewable energy. However, multiple uncertainties on the market side, load side and generation side affect the bidding plans and operation efficiency of a VPP. In this paper, a two-stage interval robust optimization model is established to optimize the bidding plans of a VPP including gas turbine, energy storage, photovoltaic (PV) and electric vehicles (EVs). Interval numbers generated by the data-driven model are used to describe the uncertainty and correlation of electricity price in the spot market. Uncertainty sets are employed to describe the uncertainties in the number of EVs and PV power generation. The objective of the model is to jointly optimize the cost of VPP participating in the spot market considering arbitrage opportunity. The objective function containing interval numbers is transformed into a solvable form based on a ranking method considering pessimistic decisions. To solve this model, an improved column-and-constraint generation (C&CG) algorithm is developed based on the combination method of genetic algorithm (GA) and solver Gurobi. The results show that the interval numbers of electricity price generated by the data-driven model proposed in this paper can reduce the cost fluctuation of VPP by 3.2%. The two-stage interval robust model proposed in this paper can reduce the cost of VPP by 1.4% compared with the conventional single-stage robust method, and lessen the cost by 35.2% compared with the robust method that does not consider arbitrage opportunities in day-ahead and real-time markets. The improved C&CG algorithm presents superior performance in convergence and accuracy. Compared to the stochastic optimization method that generates n scenarios, the computational time of the model with the interval optimization method introduced in this paper can be reduced to 1∕n. Results from case studies illust

关键词： Digital storage

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Data-Driven Interval Robust Optimization Method of Vpp Bidding Strategy in Spot Market Under Multiple Uncertainties

SSRN

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SSRN 2024年

Virtual power plant (VPP) participating in the spot market can improve the flexibility of new-type power systems with the increasing penetration of renewable energy. However, multiple uncertainties on the market side, load side and generation side affect the bidding plans and operation efficiency of a VPP. In this paper, a two-stage interval robust optimization model is established to optimize the bidding plans of a VPP including gas turbine, energy storage, photovoltaic (PV) and electric vehicles (EVs). Interval numbers generated by the data-driven model are used to describe the uncertainty and correlation of electricity price in the spot market. Uncertainty sets are employed to describe the uncertainties in the number of EVs and PV power generation. The objective of the model is to jointly optimize the cost of VPP participating in the spot market considering arbitrage opportunity. The objective function containing interval numbers is transformed into a solvable form based on a ranking method considering pessimistic decisions. To solve this model, an improved column-and-constraint generation (C&CG) algorithm is developed based on the combination method of genetic algorithm (GA) and solver Gurobi. The results show that the interval numbers of electricity price generated by the data-driven model proposed in this paper can reduce the cost fluctuation of VPP by 3.2%. The two-stage interval robust model proposed in this paper can reduce the cost by 1.4% compared with the single-stage robust method, and lessen the cost by 35.2% compared with the robust method that does not consider arbitrage opportunities in day-ahead and real-time markets. The improved C&CG algorithm presents superior performance in convergence and accuracy. Compared to the stochastic optimization method that generates n scenarios, the computational time of the model with the interval optimization method introduced in this paper can be reduced to 1∕n. Results from case studies illustrate the effectivene

关键词： Digital storage

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Distributed Momentum-based Frank-Wolfe Algorithm for Stochastic Optimization

arXiv

引用

arXiv 2022年

作者： Hou, Jie Zeng, Xianlin Wang, Gang Sun, Jian Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The School of Electronic and Information Engineering Tongji University Shanghai200082 China

—This paper considers distributed stochastic optimization, in which a number of agents cooperate to optimize a global objective function through local computations and information exchanges with neighbors over a network. Stochastic optimization problems are usually tackled by variants of projected stochastic gradient descent. However, projecting a point onto a feasible set is often expensive. The Frank-Wolfe (FW) method has well-documented merits in handling convex constraints, but existing stochastic FW algorithms are basically developed for centralized settings. In this context, the present work puts forth a distributed stochastic Frank-Wolfe solver, by judiciously combining Nesterov’s momentum and gradient tracking techniques for stochastic convex and nonconvex optimization over networks. It is shown that the convergence rate 1 of the proposed algorithm is O(k− 2) for convex optimization, and O(1/log2(k)) for nonconvex optimization. The efficacy of the algorithm is demonstrated by numerical simulations against a number of competing alternatives. Copyright © 2022, The Authors. All rights reserved.

关键词： Momentum

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Event-triggered Observability: A Set-membership Perspective

arXiv

引用

arXiv 2022年

作者： Zheng, Kaikai Shi, Dawei Chen, Tongwen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

This work attempts to discuss the observability of linear time-invariant systems with event-triggered measurements. A new notion of observability, namely, ǫ-observability is defined with parameter ǫ, which relates to the worst-case performance of inferring the initial state based on not only the received measurement but also the implicit information in the event-triggering conditions at no-event instants. A criterion is developed to test the proposed ǫ-observability of discrete-time linear systems, based on which an iterative event-triggered set-membership observer is designed to evaluate a set containing all possible values of the state. The proposed set-membership observer is designed as the outer approximation of the ellipsoids predicted based on previous state estimates and the ellipsoids inferred by fusing the received measurement and communication conditions, which is optimal in the sense of trace at each step and is proved to be asymptotically bounded. The efficiency of the proposed event-triggered set-membership state observer is verified by numerical experiments. © 2022, CC BY.

关键词： State estimation

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