Deception attacks are regarded as the most typical cyber attacks, which may damage
system performance or even cause system paralysis. Deception signals are well-designed …

Recently, preserving privacy and reducing energy consumption become important concerns
of sensor networks. However, existing privacy‐preserving estimation methods cause many …

This paper investigates the output feedback-based flocking control problem for nonlinear
dynamical systems (NDSs). To address this, distributed observers and consensus-based …

This letter focuses on the accuracy of LiDAR-inertial odometry (LIO). We propose a novel
high-precision tightly-coupled LIO method, SI-LIO, based on the invariant extended Kalman …

The evaluation of time-varying states furnishes critical data for the control design, reliability
analysis, and intelligent decision-making in the operation of robotic manipulators. The …

This paper gives a bibliometric summary of Unscented Kalman Filter (UKF) in AI-infused
robotics, highlighting its role in unifying control and cognition. Using a systematic approach …

This paper studies the problem of distributed state estimation (DSE) over sensor networks
on matrix Lie groups, which is crucial for applications where system states evolve on Lie …

This paper presents a novel approach to distributed pose estimation in the multi-agent
system based on an invariant Kalman filter with covariance intersection. Our method models …

This study delves into the Extended Kalman Filter's (EKF) use in ocean science through a
detailed bibliometric and text mining examination. Tracing its roots back to the original …

This paper investigates the design of distributed Kalman filter for large-scale systems with
state equality constraints in a Gaussian environment. Firstly, we design a unconstrained …