The Temporal Knowledge Graph(TKG) reasoning is an imperative task for various applications of TKG. However, reasoning over TKGs which aims to predict future facts has been less explored. Intuitively, entities and rela...
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In urban driving scenarios,owing to the presence of multiple static obstacles such as parked cars and roadblocks,planning a collision-free and smooth path remains a challenging *** addition,the path-planning problem i...
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In urban driving scenarios,owing to the presence of multiple static obstacles such as parked cars and roadblocks,planning a collision-free and smooth path remains a challenging *** addition,the path-planning problem is mostly non-convex,and contains multiple local ***,a method for combining a sampling-based method and an optimization-based method is proposed in this paper to generate a collision-free path with kinematic constraints for urban *** sampling-based method constructs a search graph to search for a seeding path for exploring a safe driving corridor,and the optimization-based method constructs a quadratic programming problem considering the desired state constraints,continuity constraints,driving corridor constraints,and kinematic constraints to perform path *** experimental results show that the proposed method is able to plan a collision-free and smooth path in real time when managing typical urban scenarios.
Automatic diagnosis of Coronavirus disease 2019 (COVID-19) using chest computed tomography (CT) images is of great significance for preventing its spread. However, it is difficult to precisely identify COVID-19 due to...
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Path following refers to traveling along the desired path with automatic steering control,which is a crucial technology for automatic driving *** in private areas are highly irregular,resulting in a large curvature va...
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Path following refers to traveling along the desired path with automatic steering control,which is a crucial technology for automatic driving *** in private areas are highly irregular,resulting in a large curvature variation,which reduces the control accuracy of the path following.A curvature adaptive control(CAC)based path-following method was proposed to solve the problem mentioned ***,CAC takes advantage of the complementary characteristics in response to the path curvature fluctuation of pure pursuit and front-wheel feedback and by combining the two methods further enhances the immunity of the control accuracy in response to a curvature *** CAC,the quantitative indices of the path curvature fluctuation and control accuracy were *** model between the path curvature fluctuation and a dynamic parameter was identified using the quantitative index of the control accuracy as the optimization *** experimental results of a real vehicle indicate that the control accuracy of path following is further enhanced by its immunity in response to curvature fluctuation improved by the *** addition,CAC is easy to deploy and requires low demand for hardware resources.
To improve the performance of industrial cyber-physical systems (ICPS), the joint design of control and transmission has been shown to be an effective mechanism. However, the existing joint design work lack completene...
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Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a ...
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Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a loss ***,the imbalance of the loss function caused by parameter settings usually makes it difficult for PINNs to converge,*** they fall into local *** other words,the presence of balanced PDE loss,initial loss and boundary loss may be critical for the *** addition,existing PINNs are not able to reveal the hidden errors caused by non-convergent boundaries and conduction errors caused by the PDE near the ***,these problems have made PINN-based methods of limited use on practical *** this paper,we propose a novel physics-informed neural network,*** adaptive physics-informed neural network with a two-stage training *** algorithm adds spatio-temporal coefficient and PDE balance parameter to the loss function,and solve PDEs using a two-stage training process:pre-training and formal *** pre-training step ensures the convergence of boundary loss,whereas the formal training process completes the solution of PDE by balancing various loss *** order to verify the performance of our method,we consider the imbalanced heat conduction and Helmholtz equations often appearing in practical *** Klein-Gordon equation,which is widely used to compare performance,reveals that our method is able to reduce the hidden *** results confirm that our algorithm can effectively and accurately solve models with unbalanced loss function,hidden errors and conduction *** codes developed in this manuscript are publicy available at https://***/callmedrcom/ATPINN.
作者：
SU YiminWANG LinDepartment of Automation
Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China
Autonomous vehicles must pass effective standard tests to verify their reliability and ***-ingly,it is very important to establish a complete scientific test and evaluation system for autonomous vehicles.A comprehensi...
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Autonomous vehicles must pass effective standard tests to verify their reliability and ***-ingly,it is very important to establish a complete scientific test and evaluation system for autonomous vehicles.A comprehensive framework incorporating the design of test scenarios,selection of evaluation indexes,and estab-lishment of an evaluation system is proposed in this *** aims of the system are to obtain an objective and quantitative score regarding the intelligence of autonomous vehicles,and to form an automated process in the future *** proposed framework is built on a simulation platform to ensure the feasibility of the design and implementation of the test *** design principle for the test scenarios is also *** reduce subjective influences,the proposed framework selects objective indexes from four aspects:safety,comfort,driving performance,and standard *** order relation analysis method is adopted to formulate the index weights,and fuzzy comprehensive evaluation is used to quantify the ***,a numerical example is provided to visually demonstrate the evaluation results for the autonomous vehicles scored by the proposed framework.
Fault diagnosis and prognosis in discrete event systems are studied in the scenario where the observations are possibly received with delay. To address this scenario, two conditions for diagnosis and prognosis with de...
Tractor-trailer vehicles,which are composed of a car-like tractor towing a passive trailer,have been widely deployed in the transportation industry,and trajectory planning is a critical step in enabling such a system ...
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Tractor-trailer vehicles,which are composed of a car-like tractor towing a passive trailer,have been widely deployed in the transportation industry,and trajectory planning is a critical step in enabling such a system to drive *** to the properties of being highly nonlinear and nonholonomic with complex dynamics,the tractor-trailer system poses great challenges to the development of motion-planning *** this study,an indirect trajectory planning framework for a tractor-trailer vehicle under on-road driving is presented to deal with the problem that the traditional planning framework cannot consider the feasibility and quality simultaneously in real-time trajectory generation of the tractor-trailer *** indirect planning framework can easily handle complicated tractor-trailer dynamics and generate high-quality,obstacle-free trajectory using quintic polynomial spline,speed profile optimization,forward simulation,and properly designed cost *** under different driving scenarios and trajectories with different driving requirements are conducted to validate the performance of the proposed framework.
作者：
Zhu, JiajieYang, BoCai, MingxuanDepartment of Automation
Shanghai Jiao Tong University shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China
Accurate voltage prediction for all-vanadium redox batteries (VRBs) affects the efficiency and safety of battery. In this paper, we propose a self-attention-based dual-stream neural network (SA-DSNN) model for voltage...
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