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SSRN 2023年

作者： Xiong, Yonghua Zeng, Hongrui Yu, Anjun Hiroaki, Kurokawa She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Jiangxi Ganyue Expressway Co. Ltd. Jiangxi330200 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

Due to the surge in takeaway demand, full-time delivery riders are facing challenges in completing their tasks on time. To address this issue, this study proposed a takeaway delivery method based on Crowdsensing. This strategy uses idle bicycle riders as resources to complete delivery tasks at a lower cost. To decrease the total delivery cost of merchants, the idle bicycle path planning model was established. The path planning problem of the proposed model is characterized by multiple riders, random locations, open deliveries, and pickup and delivery crossovers. Further, it belongs to the NP-hard problem. To solve this path planning model, a takeaway delivery-based genetic algorithm was designed. Order-preserving initialization was utilized to construct the initial population. The order crossover algorithm and adaptive mutation algorithm were introduced to overcome slow convergence and prevent the probability of falling into the local optimal solution of the traditional algorithm. The experimental results showed that the proposed takeaway delivery-based genetic algorithm had a fast convergence and high accuracy. Moreover, it can effectively solve the path planning model, thereby reducing merchant delivery cost and improving delivery timeliness. The method proposed in this paper has a significant application value. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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FFPA-Net: Efficient Feature Fusion with Projection Awareness for 3D Object Detection

arXiv

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arXiv 2022年

作者： Jiang, Chaokang Wang, Guangming Wu, Jinxing Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China

Promising complementarity exists between the texture features of color images and the geometric information of LiDAR point clouds. However, there still present many challenges for efficient and robust feature fusion in the field of 3D object detection. In this paper, first, unstructured 3D point clouds are filled in the 2D plane and 3D point cloud features are extracted faster using projection-aware convolution layers. Further, the corresponding indexes between different sensor signals are established in advance in the data preprocessing, which enables faster cross-modal feature fusion. To address LiDAR points and image pixels misalignment problems, two new plug- and-play fusion modules, LiCamFuse and BiLiCamFuse, are proposed. In LiCamFuse, soft query weights with perceiving the Euclidean distance of bimodal features are proposed. In BiLiCamFuse, the fusion module with dual attention is proposed to deeply correlate the geometric and textural features of the scene. The quantitative results on the KITTI dataset demonstrate that the proposed method achieves better feature-level fusion. In addition, the proposed network shows a shorter running time compared to existing methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem

Cooperative robust output regulation for second-order nonlin...

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IEEE Annual Conference on Decision and control

作者： Yi Dong Jie Chen Jie Huang Department of Automation Chinese University of Hong Kong Shatin N.T. Hong Kong State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Department of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

The cooperative robust output regulation problem for a class of second-order nonlinear multi-agent systems with an exactly known exosystem has been studied recently. This paper further studies the same problem for a class of second-order nonlinear multi-agent systems subject to an unknown exosystem. We first show that the problem can be converted into the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model. Due to the uncertain parameter in the exosystem, the augmented system is a nonlinear multi-input system with both dynamic and static uncertainties. By combining the adaptive control technique and the robust control technique, we solve our problem by a distributed adaptive robust state feedback controller.

关键词： Multi-agent systems Mathematical model Robustness Robust control automation Electronic mail Nickel

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The Analysis of Muscle-Synergy Similarity between Walking and Pedaling Based on Variational Mode Decomposition and Non-Negative Matrix Factorization

The Analysis of Muscle-Synergy Similarity between Walking an...

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IEEE International Conference on Engineering, Technology and Innovation

作者： Wangyang Ge Jinhua She Shijie Guo Feng Wang Juan Zhao Seiichi Kawata School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Engineering Research Center of the Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies Hebei Key Laboratory of Robot Sensing and Human-Robot Interaction Tianjin China School of Mechanical Engineering Hebei University of Technology Tianjin China

ISBN: (数字)9798350362435

ISBN: (纸本)9798350362442

Pedaling lower-limb rehabilitation robots are widely used in various stages of lower-limb rehabilitation because of their high safety and low requirements for patients' lower-limb strength. Researchers found that the activation sequence of the surface electromyographic (sEMG) signals of the muscles of the lower limb during pedaling is very similar to that of walking, which makes it possible to simulate the muscle force generation during walking by changing the pedal load during pedaling training. However, most pedaling lower-limb rehabilitation robots use constant loads, and it is of great importance to study the relationship between load and muscle synergy and to design load phase angle trajectories with higher muscle synergy consistency in the walking-pedaling motion to optimize the training effect of pedal-type rehabilitation robots. In this paper, we used variational mode decomposition (VMD) and nonnegative matrix factorization (NMF) to extract the muscle synergy features in each band of sEMG during walking and pedaling and to study the similarity of pedaling and walking and the influence of pedal load on muscle synergy consistency.

关键词： Legged locomotion Training Technological innovation Time series analysis Muscles Assistive robots Feature extraction Trajectory Safety Matrix decomposition

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A Collision-Free Person-Following Approach Based on Path Planning

A Collision-Free Person-Following Approach Based on Path Pla...

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IEEE International Conference on Mechatronics and automation

作者： Lei Pang Zhiqiang Cao Junzhi Yu Weimin Zhang Xuechao Chen State Key Laboratory of Management and Control for Complex Systems Institute of Automation School of Artificial Intelligence University of Chinese Academy of Sciences BIC-ESAT College of Engineering Peking University Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Person following is a crucial capability for mobile robots in tasks of human assistance and cooperation. In this paper, a person-following approach based on path planning is proposed for mobile robots, which takes person following and obstacle avoidance into account in a unified framework. The proposed approach is comprised of a sensing module and a planning module. The sensing module with a camera and a 3D LiDAR is employed to locate the target person and perceive obstacles. For the planning module, the combination of global planner and local planner effectively outputs collision-free paths and control commands for a mobile robot to keep following the target person. Experiments were conducted to evaluate the performance of the proposed approach.

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Robust control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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Chinese automation Congress (CAC)

作者： Xiao Liu Luefeng Chen Chengda Lu Haipeng Fan Min Wu Witold Pedrycz School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Department of Computer Engineering Istinye University Istanbul Turkey

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust $H_{\infty}$ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller's effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction.

关键词： Drilling Robust control Friction Simulation Geology Velocity control Stability criteria Process control Coal Output feedback

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Dynamic power systems line outage detection using particle filter and partially observed states

arXiv

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arXiv 2021年

作者： Yang, Xiaozhou Chen, Nan Zhai, Chao The Department of Industrial Systems Engineering and Management National University of Singapore Singapore117576 Singapore ETH Zurich Future Resilient Systems Singapore-ETH Centre 1 CREATE Way CREATE Tower Singapore138602 Singapore The School of Automation China University of Geosciences Wuhan430074 China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Real-time transmission line outage detection is difficult because of partial phasor measurement unit (PMU) deployment and varying outage signal strength. Existing detection approaches focus on monitoring PMU-measured nodal algebraic states, i.e., voltage phase angle and magnitude. The success of such approaches, however, is largely predicated on strong outage signals and the presence of PMUs in the outage location's vicinity. To overcome these limitations, a unified framework is proposed in this work by utilizing both nodal voltage information and generator dynamic states, e.g., rotor angular position. The proposed scheme is shown to be faster and more robust to unknown outage locations through the incorporation of generator dynamics. Using the IEEE 39-bus system simulation data, the proposed scheme's properties and performances compared to existing approaches are presented. The new approach could help improve operators' real-time situational awareness by detecting outages faster and providing a breakdown of outage signals for diagnostic purposes, making future power systems more resilient. Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Periodic event-triggered output regulation for linear multi-agent systems

arXiv

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arXiv 2020年

作者： Zheng, Shiqi Shi, Peng Agarwal, Ramesh K. Lim, Chee Peng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Electrical and Electronic Engineering University of Adelaide AdelaideSA5005 Australia Department of Mechanical Engineering Washington University Box 1185 St Louis CampusMO63130 United States Institute for Intelligent Systems Research and Innovation Deakin University Australia

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensorto-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined a prior, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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Accurate Identification and Localization of Transmission Lines Under complex Lighting for Distribution Network Power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

引用

Chinese automation Congress (CAC)

作者： Tianhe Liu Xin Chen Chenyu Hu Xu Jian Shengzu Li Gang Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an “eye-on-hand” configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within $\pm 4\text{mm}$ , outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots.

关键词： Location awareness Visualization Power transmission lines Accuracy Image color analysis Lighting Distribution networks Grasping Wire Robots

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