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SSRN 2022年

作者： Yao, Canqi Chen, Shibo Salazar, Mauro Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology EindhovenMB 5600 Netherlands

This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers, where the operator needs to solve the routing and charging problem jointly for each EV. Hereby we consider incentive-aware customers and propose that the operator offers monetary incentives to customers in exchange for time flexibility. In this way, the fleet operator can achieve a routing and charging schedule with lower costs, whilst the customers receive monetary compensation for their flexibility. Specifically, we first propose a bi-level optimization model whereby the fleet operator optimizes the routing and charging schedule accounting for the spatio-temporal varying charging price, jointly with a monetary incentive to reimburse the delivery time flexibility experienced by the customers. Concurrently the customers choose their own time flexibility by minimizing their own cost. Second, we cope with the computational burden coming from this nonlinear bi-level optimization model with an accurate reformulation approach consisting of the KKT optimality conditions, a Big-M-based linearization method, and the zero duality gap of convex optimization problems. This way, we convert the proposed problem into a single-level optimization problem, which can be solved by a strengthened generalized Benders decomposition method holding a faster convergence rate than the generalized Benders decomposition method. To evaluate the effectiveness of the proposed mathematical model, we carry out numerous simulation experiments by using the VRP-REP data of Belgium. The numerical results showcase that the proposed mathematical model can reduce the delivery fees for the customers together with the cost of operation incurred by the fleet operator. © 2022, The Authors. All rights reserved.

关键词： Sales

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Joint Routing and Charging Problem of Electric Vehicles with Incentive-aware Customers Considering Spatio-temporal Charging Prices

arXiv

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arXiv 2022年

关键词： Sales

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AI Enabled Automatic Mobile Robot Intelligent Navigation in Construction with Obstacle Awareness

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IEEE Transactions on Automation Science and engineering 2025年

作者： Zhang, Yinlong Liu, Yuanhao Cui, Yunge Zeng, Ziming Liang, Wei Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China University of Chinese Academy of Sciences Beijing101408 China Zeekr Group Zeekr Intelligent Driving Department Shanghai110078 China Shenzhen Polytechnic University School of Automotive and Transportation Engineering Shenzhen518055 China

In the construction industry, the integration of artificial intelligence (AI) and robotics has led to significant advancements in automating various tasks. One critical aspect is the intelligent navigation of automatic mobile robot (AMR) within construction sites, where dynamic environments pose challenges such as inaccurate robot state estimation, irregular and textureless obstacle detection. To solve these issues, this paper designs an AI enabled obstacle-aware AMR intelligent navigation approach while ensuring robot safety and efficiency. Specifically, the robot is equipped with the complementary RGB camera, inertial measurement unit (IMU) and wheel encoder to estimate the states (i.e., positions, orientations and velocities), which have been tightly fused in the optimization framework. Furthermore, the RGB-Depth images are jointly fed into the AI model. It combines of Mask-RCNN and multi-scale attention network, to detect and segment the obstacles, and estimate the corresponding relative depth. It should be noted that the system incorporates obstacle awareness mechanisms to dynamically switch the robot's velocities in response to obstacles in the environment, ensuring smooth and collision-free movement. Experimental results demonstrate the effectiveness and robustness of the proposed AI-enabled navigation system in real-world construction scenarios, showcasing its potential to enhance productivity and safety in construction automation. © 2004-2012 IEEE.

关键词： Construction industry

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Corpuscular Volume Estimation Using a Small Amount of Blood via Microscope Images

Corpuscular Volume Estimation Using a Small Amount of Blood ...

引用

International Conference on control, Automation and Systems ( ICCAS)

作者： Jegyeong Ryu Dahyun Nam Junghyun John Son Amy Kyungwon Han Deukhee Lee Department of Mechanical Engineering Seoul National University Seoul Republic of Korea Center for Healthcare Robotics Korea Institute of Science and Technology Seoul Republic of Korea Division of Mechanical Engineering Yonsei University Seoul Republic of Korea Doping Control Center Korea Institute of Science and Technology Seoul Republic of Korea Division of AI-Robotics KIST School University of Science and Technology Seoul Republic of Korea Yonsei-KIST Convergence Research Institute Yonsei University Seoul Republic of Korea

Blood is an analysis serves as a valuable diagnostic tool that can easily and simply diagnose health, and in particular, red blood cells (RBC) or hematocrit (Hct) and mean corpuscular volume (MCV) can diagnose various diseases. Electrochemical methods have been proposed to find out RBC, Hct, and MCV, but it is difficult to use them for infants or the elderly because they require a large amount of blood. As an alternative, method like blood smear has been suggested to make a diagnosis with a small amount of blood, but it takes a long time to dry the sample. In this study, we present a methodology to make the simple and quick blood analysis. This method uses a microscope image of a small amount of blood, without drying the blood sample. From the image, in order to detect all the blood cells, we adopt a loop algorithm consist of concave point detection, ellipse fitting, and blob detection. To assess the validity and accuracy of the proposed method, an investigation is conducted to examine its correlation with the Sysmex XN-1000, a widely utilized medical reference standard; we show that the correlation coefficients are higher than 0.88, showing more correlation than the method in previous studies by comparing the estimation results. By developing this method, it will be possible to establish a simple quick blood analysis method using microscope images, decreasing a time consumed for the health checkup, saving more lives.

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Coordinated Guiding Vector Field Design for Ordering-Flexible Multi-Robot Surface Navigation

arXiv

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arXiv 2024年

作者： Hu, Bin-Bin Zhang, Hai-Tao Yao, Weijia Sun, Zhiyong Cao, Ming The School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China The School of Robotics Hunan University Hunan410082 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands Department of Electrical Engineering Eindhoven University of Technology Netherlands

We design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired two-dimensional (2D) surface. The CGVF is characterized by three terms, i.e., a convergence term to drive the robots to converge to the desired surface, a propagation term to provide a traversing direction for maneuvering on the desired surface, and a coordinated term to achieve the surface motion coordination with an arbitrary ordering of the robotic group. By setting the surface parameters as additional virtual coordinates, the proposed approach eliminates potential singularity of the CGVF and enables both the global convergence to the desired surface and the maneuvering on the surface from all possible initial conditions. The ordering-flexible surface motion coordination is realized by each robot to share with its neighbors only two virtual coordinates, i.e. that of a given target and that of its own, which reduces the communication and computation cost in multi-robot surface navigation. Finally, the effectiveness of the CGVF is substantiated by extensive numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Navigation

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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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Fluid pumping by liquid metal droplet utilizing ac electric field

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Physical Review E 2022年第2期105卷 025102-025102页

作者： Chun-Lei Song Ye Tao Wei-Yu Liu Yi-Cheng Chen Rui Xue Tian-Yi Jiang Biao Li Hong-Yuan Jiang Yu-Kun Ren State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China School of Engineering and Applied Sciences and Department of Physics Harvard University Cambridge Massachusetts 02138 USA School of Electronics and Control Engineering Chang'an University Xi'an 710000 China School of Energy Science and Engineering Harbin Institute of Technology Harbin 150001 China School of Mechatronics Engineering Harbin Institute of Technology Harbin 150001 China

We report a unique phenomenon in which liquid metal droplets (LMDs) under a pure ac electric field pump fluid. Unlike the directional pumping that occurs upon reversing the electric field polarity under a dc signal, this phenomenon allows the direction of fluid motion to be switched by simply shifting the position of the LMD within the cylindrical chamber. The physical mechanism behind this phenomenon has been termed Marangoni flow, caused by nonlinear electrocapillary stress. Under the influence of a localized, asymmetric ac electric field, the polarizable surface of the position-offset LMD produces a net time-averaged interfacial tension gradient that scales with twice the field strength, and thus pumps fluid unidirectionally. However, the traditional linear RC circuit polarization model of the LMD/electrolyte interface fails to capture the correct pump-flow direction when the thickness of the LMD oxide skin is non-negligible compared to the Debye length. Therefore, we developed a physical description by treating the oxide layer as a distributed capacitance with variable thickness and connected with the electric double layer. The flow profile is visualized via microparticle imaging velocimetry, and excellent consistency is found with simulation results obtained from the proposed nonlinear model. Furthermore, we investigate the effects of relevant parameters on fluid pumping and discuss a special phenomenon that does not exist in dc control systems. To our knowledge, no previous work addresses LMDs in this manner and uses a zero-mean ac electric field to achieve stable, adjustable directional pumping of a low-conductivity solution.

关键词： Electrokinetic flows Interfacial flows Surface tension effects Lagrangian particle tracking

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Learn to efficiently exploit cost maps by combining RRT* with Reinforcement Learning

Learn to efficiently exploit cost maps by combining RRT* wit...

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IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Riccardo Franceschini Matteo Fumagalli Julian Cayero Becerra Eurecat Centre Tecnològic de Catalunya Robotics and Automation Unit Cerdanyola del Valles Barcelona Spain Department of Electrical Engineering Automation and Control group Danish Technical University Elektrovej Lyngby Denmark

ISBN: (纸本)9781665456814

Safe autonomous navigation of robots in complex and cluttered environments is a crucial task and is still an open challenge even in 2D environments. Being able to efficiently minimize multiple constraints such as safety or battery drain requires the ability to understand and leverage information from different cost maps. Rapid-exploring random trees (RRT) methods are often used in current path planning methods, thanks to their efficiency in finding a quick path to the goal. However, these approaches suffer from a slow convergence towards an optimal solution, especially when the planner's goal must consider other aspects like safety or battery consumption besides simply achieving the goal. Therefore, it is proposed a sample-efficient and cost-aware sampling RRT* method that can overcome previous methods by exploiting the information gathered from map analysis. In particular, the use of a Reinforcement Learning agent is leveraged to guide the RRT* sampling toward an almost optimal solution. The performance of the proposed method is demonstrated against different RRT* implementations in multiple synthetic environments.

关键词： Costs Three-dimensional displays Reinforcement learning Robot sensing systems Path planning Safety Batteries

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Unsupervised Video Anomaly Detection with Self-Attention Based Feature Aggregating

Unsupervised Video Anomaly Detection with Self-Attention Bas...

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International Conference on Intelligent Transportation

作者： Zhenhao Ye Yanlong Li Zhichao Cui Yuehu Liu Li Li Le Wang Chi Zhang National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an Shaanxi China School of Software Engineering Xi'an Jiaotong University Xi'an Shaanxi China School of Electronics and Control Engineering Chang'an University Department of Automation BNRist Tsinghua University Beijing China

Anomaly detection in surveillance videos is a crucial and challenging task in the intelligent transportation systems. Previous methods utilize a memory module to store prototypical feature embeddings as normal patterns learned from normal training data. However, due to the complexity of real-world scenarios, it is difficult to choose an appropriate size of memory module which can not only memorize normal patterns comprehensively, but also capable of dealing with unseen normal scenarios. To tackle this problem, we learn normal video patterns by constructing and exploring correlations between visual semantics. In the training stage, we act the self-attention map between embeddings as a description of information association between different visual semantics. A self-attention based feature aggregating module is designed to regenerate a feature map through aggregating embeddings with similar information based on the attention map. By decoding the generated feature map instead of the original one to predict the future frame of the input video clip, the model learns to build strong information association between normal visual semantics. Moreover, we observe that abnormal embeddings hardly build strong association with others. Thus, we design a feature-level anomaly criterion referred as prior deviation to increase the difference between attention maps generated by normal and abnormal frames. In the inferring stage, the proposed prior deviation jointly detects anomalies with pixel-level frame prediction error. Experiment results and ablation studies on mainstream benchmarks demonstrate the effectiveness of our design.

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Finite element hybridization of port-Hamiltonian systems

arXiv

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arXiv 2023年

作者： Brugnoli, Andrea Rashad, Ramy Zhang, Yi Stramigioli, Stefano ICA Université de Toulouse ISAE–SUPAERO INSA CNRS MINES ALBI UPS Toulouse France Control and Instrumentation Engineering Department King Fahd University of Petroleum and Minerals Saudi Arabia School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China Robotics and Mechatronics Department University of Twente Netherlands

In this contribution, we extend the hybridization framework for the Hodge Laplacian [Awanou et al., Hybridization and postprocessing in finite element exterior calculus, 2023] to port-Hamiltonian systems describing linear wave propagation phenomena. To this aim, a dual field mixed Galerkin discretization is introduced, in which one variable is approximated via conforming finite element spaces, whereas the second is completely local. The mixed formulation is then hybridized to obtain an equivalent formulation that can be more efficiently solved using a static condensation procedure in discrete time. The size reduction achieved thanks to the hybridization is greater than the one obtained for the Hodge Laplacian as the final system only contains the globally coupled traces of one variable. Numerical experiments on the 3D wave and Maxwell equations illustrate the convergence of the method and the size reduction achieved by the hybridization. © 2023, CC BY-NC-ND.

关键词： Maxwell equations

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