Papers State Estimation
“State Estimation” 태그가 달린 논문 1,067편 · 필터 해제
Privacy-Preserving Fusion for Multi-Sensor Systems Under Multiple Packet Dropouts
Wireless sensor networks (WSNs) are critical components in modern cyber-physical systems, enabling efficient data collection and fusion through spatially distributed sensors. However, the inherent risks of eavesdropping …
Privacy PreservingState EstimationDistributed Resilient State Estimation and Control with Strategically Implemented Security Measures
This paper addresses the problem of distributed resilient state estimation and control for linear time-invariant systems in the presence of malicious false data injection sensor attacks and bounded noise. We consider a s…
State EstimationRecurrent neural network-based robust control systems with closed-loop regional incremental ISS and application to MPC design
This paper investigates the design of output-feedback schemes for systems described by a class of recurrent neural networks. We propose a procedure based on linear matrix inequalities for designing an observer and a stat…
State EstimationDRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy
With the increasing presence of automated vehicles on open roads under driver supervision, disengagement cases are becoming more prevalent. While some data-driven planning systems attempt to directly utilize these diseng…
Autonomous DrivingState EstimationProbabilistic Trajectory GOSPA: A Metric for Uncertainty-Aware Multi-Object Tracking Performance Evaluation
This paper presents a generalization of the trajectory general optimal sub-pattern assignment (GOSPA) metric for evaluating multi-object tracking algorithms that provide trajectory estimates with track-level uncertaintie…
Multi-Object TrackingObject TrackingState EstimationvalidBayesian Knowledge Transfer for a Kalman Fixed-Lag Interval Smoother
A Bayesian knowledge transfer mechanism that leverages external information to improve the performance of the Kalman fixed-lag interval smoother (FLIS) is proposed. Exact knowledge of the external observation model is as…
State EstimationTransfer LearningROSA: Harnessing Robot States for Vision-Language and Action Alignment
Vision-Language-Action (VLA) models have recently made significant advance in multi-task, end-to-end robotic control, due to the strong generalization capabilities of Vision-Language Models (VLMs). A fundamental challeng…
State EstimationVision-Language-ActionA Novel ViDAR Device With Visual Inertial Encoder Odometry and Reinforcement Learning-Based Active SLAM Method
In the field of multi-sensor fusion for simultaneous localization and mapping (SLAM), monocular cameras and IMUs are widely used to build simple and effective visual-inertial systems. However, limited research has explor…
Deep Reinforcement LearningSensor FusionSimultaneous Localization and MappingState EstimationObserver Switching Strategy for Enhanced State Estimation in CSTR Networks
Accurate state estimation is essential for monitoring and controlling nonlinear chemical reactors, such as continuous stirred-tank reactors (CSTRs), where limited sensor coverage and process uncertainties hinder real-tim…
Fault DetectionState EstimationBridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Vehicle state estimation presents a fundamental challenge for autonomous driving systems, requiring both physical interpretability and the ability to capture complex nonlinear behaviors across diverse operating condition…
Autonomous DrivingState EstimationUncertainty QuantificationRecursive KalmanNet: Deep Learning-Augmented Kalman Filtering for State Estimation with Consistent Uncertainty Quantification
State estimation in stochastic dynamical systems with noisy measurements is a challenge. While the Kalman filter is optimal for linear systems with independent Gaussian white noise, real-world conditions often deviate fr…
State EstimationUncertainty QuantificationHarvest and Jam: Optimal Self-Sustainable Jamming Attacks against Remote State Estimation
This paper considers the optimal power allocation of a jamming attacker against remote state estimation. The attacker is self-sustainable and can harvest energy from the environment to launch attacks. The objective is to…
State EstimationImproved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States
We propose a hybrid variational framework that enhances Neural Quantum States (NQS) with a Normalising Flow-based sampler to improve the expressivity and trainability of quantum many-body wavefunctions. Our approach deco…
State EstimationRobust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications
State estimation or filtering serves as a fundamental task to enable intelligent decision-making in applications such as autonomous vehicles, robotics, healthcare monitoring, smart grids, intelligent transportation, and …
Autonomous VehiclesBayesian InferenceIndoor LocalizationPoint Cloud Registration+2Conformal Safety Shielding for Imperfect-Perception Agents
We consider the problem of safe control in discrete autonomous agents that use learned components for imperfect perception (or more generally, state estimation) from high-dimensional observations. We propose a shield con…
Conformal PredictionState EstimationThe Invariant Zonotopic Set-Membership Filter for State Estimation on Groups
The invariant filtering theory based on the group theory has been successful in statistical filtering methods. However, there exists a class of state estimation problems with unknown statistical properties of noise distu…
State EstimationDirect Integration of Recursive Gaussian Process Regression Into Extended Kalman Filters With Application to Vapor Compression Cycle Control
This paper presents a real-time capable algorithm for the learning of Gaussian Processes (GP) for submodels. It extends an existing recursive Gaussian Process (RGP) algorithm which requires a measurable output. In many a…
Gaussian ProcessesState EstimationThe Geometry of Extended Kalman Filters on Manifolds with Affine Connection
The extended Kalman filter (EKF) has been the industry standard for state estimation problems over the past sixty years. The classical formulation of the EKF is posed for nonlinear systems defined on global Euclidean spa…
State EstimationTopology-Aware Graph Neural Network-based State Estimation for PMU-Unobservable Power Systems
Traditional optimization-based techniques for time-synchronized state estimation (SE) often suffer from high online computational burden, limited phasor measurement unit (PMU) coverage, and presence of non-Gaussian measu…
Graph AttentionGraph Neural NetworkState EstimationRecursive Privacy-Preserving Estimation Over Markov Fading Channels
In industrial applications, the presence of moving machinery, vehicles, and personnel, contributes to the dynamic nature of the wireless channel. This time variability induces channel fading, which can be effectively mod…
Privacy PreservingState Estimation