This work aims to present a three-dimensional vehicle dynamics state estimation under varying signal quality. Few researchers have investigated the impact of three-dimensional road geometries on the state estimation a...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
This work aims to present a three-dimensional vehicle dynamics state estimation under varying signal quality. Few researchers have investigated the impact of three-dimensional road geometries on the state estimation and, thus, neglect road inclination and banking. Especially considering high velocities and accelerations, the literature does not address these effects. Therefore, we compare two- and three-dimensional state estimation schemes to outline the impact of road geometries. We use an Extended Kalman Filter with a point-mass motion model and extend it by an additional formulation of reference angles. Furthermore, virtual velocity measurements significantly improve the estimation of road angles and the vehicle’s side slip angle. We highlight the importance of steady estimations for vehicle motion control algorithms and demonstrate the challenges of degraded signal quality and Global Navigation Satellite System dropouts. The proposed adaptive covariance facilitates a smooth estimation and enables stable controller behavior. The developed state estimation has been deployed on a high-speed autonomous race car at various racetracks. Our findings indicate that our approach outperforms state-of-the-art vehicle dynamics state estimators and an industry-grade Inertial Navigation System. Further studies are needed to investigate the performance under varying track conditions and on other vehicle types.
Fundamental machine learning theory shows that different samples contribute unequally to both the learning and testing *** studies on deep neural networks(DNNs)suggest that such sample differences are rooted in the di...
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Fundamental machine learning theory shows that different samples contribute unequally to both the learning and testing *** studies on deep neural networks(DNNs)suggest that such sample differences are rooted in the distribution of intrinsic pattern information,namely sample *** by recent discoveries in network memorization and generalization,we propose a pair of sample regularity measures with a formulation-consistent representation for both ***,the cumulative binary training/generalizing loss(CBTL/CBGL),the cumulative number of correct classifications of the training/test sample within the training phase,is proposed to quantify the stability in the memorization-generalization process,while forgetting/mal-generalizing events(ForEvents/MgEvents),i.e.,the misclassification of previously learned or generalized samples,are utilized to represent the uncertainty of sample regularity with respect to optimization *** effectiveness and robustness of the proposed approaches for mini-batch stochastic gradient descent(SGD)optimization are validated through sample-wise *** training/test sample selection applications show that the proposed measures,which share the unified computing procedure,could benefit both tasks.
Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been p...
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Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.
The performance of environment perception in autonomous vehicles is significantly influenced by the sensor setup, which is determined in the early design phase. The selection of the type and position of sensors in thi...
The performance of environment perception in autonomous vehicles is significantly influenced by the sensor setup, which is determined in the early design phase. The selection of the type and position of sensors in this phase often occurs before the availability of data processing algorithms. Therefore, the evaluation of the sensor setup can only be based on coverage metrics. This paper presents a novel framework for modeling the sensor coverage of autonomous vehicles. By discretizing the environment into grid cells, our framework analyzes each sensor and the whole setup. Our methodology systematically determines the coverage, identifies redundancy and blind spot areas, and obtains quantifiable metrics for evaluating the sensor setup efficiency. Utilizing the PyVista visualization library, we present the individual building blocks of the framework and their open-source implementation. The results from a real-world case study demonstrate our framework’s ability to identify weaknesses in sensor setup coverage. Our approach helps to develop a comprehensive understanding of the sensor coverage and, therefore, contributes to designing more effective and reliable sensing systems.
Despite some efforts and attempts have been made to improve the direction-of-arrival (DOA) estimation performance of the standard Capon beamformer (SCB) in array processing, rigorous statistical performance analyses o...
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Tuberculosis remains a significant global problem. The modification in smart technology (ST) invention generates novel chances to reform tuberculosis (TB) controlling. This work explores the potential of ST for filter...
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This work investigates the integration of complementary FET (CFET) transistors within static random-access memory (SRAM) to deliver aggressive bitcell area scaling and substantial performance gains for deeply scaled C...
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ISBN:
(数字)9798331504168
ISBN:
(纸本)9798331504175
This work investigates the integration of complementary FET (CFET) transistors within static random-access memory (SRAM) to deliver aggressive bitcell area scaling and substantial performance gains for deeply scaled CMOS nodes beyond 3nm. By vertically stacking the pFET atop the nFET, CFETs achieve a profound reduction in the cell area, presenting a viable pathway to meet extreme density demands. Utilizing the industry-standard BSIM-CMG model, we carefully calibrate the CFET device's electrical characteristics against measurements from fabricated devices. Our calibrated model is then applied to a 6T-SRAM cell and critical peripheral circuits, including pre-charge, sense amplifier, and latch configurations. Comprehensive SPICE simulations enable a detailed assessment of SRAM performance, quantifying noise margins, access delays, and power dissipation across both read and write cycles. Our analysis further dissects the delay and power contributions along the signal path, underscoring CFET's transformative potential in advancing SRAM scalability and efficiency in leading-edge technology nodes.
This work focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows a system to plan within a predefined space. In contrast to state-of-the-art meth...
This work focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows a system to plan within a predefined space. In contrast to state-of-the-art methods, we drop the assumption of a given collision-free geometric reference. Instead, we present a three-stage motion planning method that solely relies on start and goal locations and a geometric representation of the environment to compute a time-optimal trajectory that is compliant with system dynamics and constraints. The proposed scheme first finds collision-free navigation corridors, second computes an obstacle-free Pythagorean Hodograph parametric spline along each corridor, and third, solves a spatially reformulated minimum-time optimization problem at each of these corridors. The spline obtained in the second stage is not a geometric reference, but an extension of the free space associated with its corridor, and thus, time-optimality of the solution is guaranteed. The validity of the proposed approach is demonstrated by a well-established planar example and benchmarked in a spatial system against state-of-the-art methodologies across a wide range of scenarios in highly congested environments. Video: https://***/zGExvnUEfOY
This work focuses on pose-following, a variant of path-following in which the goal is to steer the system's position and attitude along a path with a moving frame attached to it. Full body motion control, while ac...
This work focuses on pose-following, a variant of path-following in which the goal is to steer the system's position and attitude along a path with a moving frame attached to it. Full body motion control, while accounting for the additional freedom to self-regulate the progress along the path is an appealing trade-off. Towards this end, we extend the well-established dual quaternion based pose-tracking method into a pose-following control law. Specifically, we derive the equations of motion for the full pose error between the geometric reference and the rigid body in the form of a dual quaternion and dual twist, and subsequently, formulate an almost globally asymptotically stable control law. The global attractivity of the presented approach is validated in a spatial example, while its benefits over pose-tracking are showcased through a planar case-study.
Validating safe and reliable interaction with vulnerable road users (VRUs) is imperative for autonomous vehicles, especially in simulation testing procedures before on-road applications. However, existing VRU agents a...
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