检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Zhang, Huaqing Ma, Hongbin Mersha, Bemnet Wondimagegnehu Zhang, Xiaofei Jin, Ying School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Beijing100081 China School of Vehicle and Mobility Tsinghua University Beijing100084 China

In search-attack and search-rescue tasks performed by multi-UAV, cooperative search plays an important part. The majority of approaches in use today assume that the UAV swarm's communication network is complete. However, these links are susceptible to environmental changes or adversary interference. Aiming at cooperative search in search-attack and search-rescue tasks, we propose a distributed cooperative search method for multi-UAV with unstable communications (DCS-UC), which is developed based on ant colony optimization (ACO). In this method, three algorithms are presented to enable the UAV swarm to conduct online cooperative search efficiently and safely. Firstly, an algorithm of pheromone matrix consensus update used in ACO is designed under switching and connected topology graphs, which can make the pheromone matrix maintained by each UAV achieve consensus, so that the cooperative efficiency of the UAV swarm is improved. Then, a position consensus update algorithm is presented where the position vector, including the positions of all the UAVs in each UAV, can achieve consensus under switching and connected topology graphs. Finally, to tackle the collision avoidance of all the UAVs, an algorithm of collision avoidance between UAVs is designed by using the obtained consistent positions of all the UAVs, which can make the UAV swarm conduct cooperative search safely. Extensive physical simulation results carried out in Gazebo verify the advantages of our multi-UAV cooperative search method. © 2023, The Authors. All rights reserved.

关键词： Ant colony optimization

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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Jiang, Jiaqi Luo, Shan Robot Perception Lab Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

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TransForce: Transferable Force Prediction for Vision-based Tactile Sensors with Sequential Image Translation

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Zhang, Xuyang Luo, Shan The Robot Perception Lab Centre for Robotics Research Department of Engineering King's College London LondonWC2R 2LS United Kingdom The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acquiring paired tactile images and force labels. In this study, we introduce a transferable force prediction model, TransForce, designed to leverage collected image-force paired data for new sensors under varying illumination colors and marker patterns while improving the accuracy of predicted forces, especially in the shear direction. Our model effectively achieves translation of tactile images from the source domain to the target domain, ensuring that the generated tactile images reflect the illumination colors and marker patterns of the new sensors while accurately aligning the elastomer deformation observed in existing sensors, which is beneficial to force prediction of new sensors. As such, a recurrent force prediction model trained with generated sequential tactile images and existing force labels is employed to estimate higher-accuracy forces for new sensors with lowest average errors of 0.69N (5.8% in full work range) in x-axis, 0.70N (5.8%) in y-axis, and 1.11N (6.9%) in z-axis compared with models trained with single images. The experimental results also reveal that pure marker modality is more helpful than the RGB modality in improving the accuracy of force in the shear direction, while the RGB modality show better performance in the normal direction. Copyright © 2024, The Authors. All rights reserved.

关键词： RGB color model

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Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

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arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Path Tracking control of Tracked Paver Based on Improved Pure Pursuit Algorithm

Path Tracking Control of Tracked Paver Based on Improved Pur...

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第40届中国控制会议

作者： Shuai Wang Shanshan Fu Bin Li Shoukun Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

This paper investigates the high-precision path tracking control of tracked paver combined with global satellite navigation *** the paver is performing paving operations,it requires high path tracking accuracy and good vehicle ***,considering the influence of road curvature on path tracking accuracy and vehicle stability,and the situation that the vehicle can not move quickly to the expectation path when the lateral position of the vehicle deviates from the expectation path,this paper proposes a lateral path tracking control method based on improved Pure Pursuit *** control method is verified through *** experimental results show that the maximum lateral tracking error of the improved algorithm is 0.04 m,which is 55.56% lower than that of the original algorithm,and the average lateral tracking error is 0.02 m,which is60% lower than that of the original *** purpose of high-precision path tracking of the paver is realized.

关键词： Tracked paver Path tracking Road curvature Pure Pursuit algorithm

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Forecasting Approach in Fuzzy Time Series Based on Information Granules

Forecasting Approach in Fuzzy Time Series Based on Informati...

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第40届中国控制会议

作者： Kaixin Zhao Yaping Dai Ye Ji Jiayi Sun School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at a large number of ambiguous,imprecise and incomplete data in the real world,fuzzy time series has come into being and developed into an effective forecasting *** the process of modeling and forecasting of fuzzy time series,the prediction performance of fuzzy time series can be effectively improved by partitioning the universe of discourse into different *** this paper,a forecasting approach for fuzzy time series,which introduces the granularity mechanism into interval division and employs differential data for incremental forecasting,is proposed to solve the problem of time series forecasting with high forecasting *** the proposed approach,in order to describe the fuzzy logic relationship and fuzzy trend of historical data,we first do differential processing on the historical ***,Fuzzy C-means(FCM) clustering algorithm is used to generate several partition intervals *** the sequel,we use the principle of justifiable granularity to constantly adjust the width of all the intervals,so that these information granules associated with corresponding intervals become the most"informative" information ***,the boundary of information granules is used as the basis of interval division to complete the forecasting *** illustrative example is provided to demonstrate the essence of the proposed *** comparative experiment with other representative approaches shows that the proposed approach can significantly improve the prediction accuracy of time series.

关键词： Fuzzy Time Series Information Granules Unequal-sized Intervals Forecasting

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A Scale Adaptive and Anti-occlusion Tracking Algorithm with Feature Fusion

A Scale Adaptive and Anti-occlusion Tracking Algorithm with ...

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第40届中国控制会议

作者： Le Li Haoyu Liao Yongqiang Bai School of Automation Beijing Institude of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institude of Technology

KCF is an excellent target tracking algorithm with fast computing speed and high ***,it performs poorly in complex tracking situations such as target deformation,motion blur,scale change and *** view of target deformation and motion blur,we designed a feature fusion method,which combines CN feature and HOG feature to enhance the expression ability of the *** view of the change of scale,the scale pool is *** improve the ability of anti occlusion,we improved the model updating mechanism and designed a SVM detector to detect the target after it is *** experiments on OTB-100 showed that the improved method achieves a great improvement compared with KCF,the accuracy increases by 4.2%,the success rate increases by 12.1%,and our algorithm meets the real-time requirements.

关键词： KCF target tracking feature fusion scale pool anti occlusion

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Long-term stable target tracking algorithm based on improved Staple

Long-term stable target tracking algorithm based on improved...

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第40届中国控制会议

作者： Haoyu Liao Le Li Yongqiang Bai School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

Staple algorithm has been widely proven to be an efficient target tracking method, but it is still easy to fail in some tracking scenarios such as target deformation, motion blur, and complete occlusion. This paper makes improvements to the above problems. First of all, we use a binary mask based on spatial reliability to enhance the target information in Staple’s color features, which improves the tracking accuracy of the algorithm in complex scenes. Secondly, we propose a response graph evaluation index based on secondary detection, that is, the least square filter is used for convolution at the original response peak to obtain a more accurate tracking state judgment. Finally, if the current state is judged to be a failure, we use a particle filter-based motion estimation method to relocate the target, thereby improving the algorithm’s tracking success rate when the target is occluded. The test results on the OTB2015 data set show that the overall accuracy of the algorithm in this paper has reached 80%, and the overall success rate has reached 73.2%, which proves the long-term stable tracking performance of the algorithm.

关键词： Target tracking Staple Binary mask Particle filter Anti-occlusion

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Dynamic Resource Scheduling Based on Improved Genetic Algorithm

Dynamic Resource Scheduling Based on Improved Genetic Algori...

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第40届中国控制会议

作者： Gui Yuanyuan School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at the problem of how to realize the reasonable distribution of goods and the resource scheduling of route planning under dynamic conditions, a phased refresh method is proposed to deal with the requirements in sections. At the same time, the clustering method is introduced to generate the initial population. And the cross and mutation rate is determined by a step-by-step reduction method, which is used to solve the problem of the traditional genetic algorithm falling into the local optimum caused by the uneven distribution of searchable solutions. Finally, the effectiveness of the improved method is verified by simulation experiments.

关键词： resource scheduling phased refresh improved genetic algorithm

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Multi-Batch Production Scheduling for Distributed Serial Lines with Unreliable Machines and Finite Buffers

Multi-Batch Production Scheduling for Distributed Serial Lin...

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第40届中国控制会议

作者： Longzhu Huang Zhiyang Jia Xiaohan Wang Jingchuan Chen School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In the modern manufacturing environment, the production systems develop towards a flexible direction due to the market demands of multiple varieties and small batch-based customized products. To make better use of the existing resources and to improve production efficiency, distributed manufacturing mode begins to appear. This paper concentrates on a multi-type production scheduling problem for distributed serial lines. Specifically, unreliable machines and finite buffers are considered,which are more realistic in the practical production. The mathematical model for the production system with two Bernoulli machines is formulated first. Then, under the hypothetical model mentioned above, the main work of this article is to propose the exact and approximate analyses to calculate the performance indicators. Based on the analysis of the model, the genetic algorithm is applied to optimize the maximum completion time on the distributed serial lines for multi-batch-based production tasks. Finally, the feasibility and effectiveness of the mathematical model and the proposed algorithm are verified through numerical experiments.

关键词： Bernoulli machine intelligent manufacturing Production scheduling Transient analysis

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