A review of Kalman filter with artificial intelligence techniques
Kalman filter (KF) is a widely used estimation algorithm for many applications. However, in
many cases, it is not easy to estimate the exact state of the system due to many reasons …
many cases, it is not easy to estimate the exact state of the system due to many reasons …
A review of Bayes filters with machine learning techniques and their applications
A Bayes filter is a widely used estimation algorithm, but it has inherent limitations.
Performance can degrade when the dynamics are highly nonlinear or when the probability …
Performance can degrade when the dynamics are highly nonlinear or when the probability …
A secure robot learning framework for cyber attack scheduling and countermeasure
The problem of learning-based control for robots has been extensively studied, whereas the
security issue under malicious adversaries has not been paid much attention to. Malicious …
security issue under malicious adversaries has not been paid much attention to. Malicious …
Deep reinforcement learning control of fully-constrained cable-driven parallel robots
Cable-driven parallel robots (CDPRs) have complex cable dynamics and working
environment uncertainties, which bring challenges to the precise control of CDPRs. This …
environment uncertainties, which bring challenges to the precise control of CDPRs. This …
Trajectory optimization and tracking control of free-flying space robots for capturing non-cooperative tumbling objects
This paper investigates the problem of capturing non-cooperative tumbling objects by free-
flying space robots. To solve the two challenges of task constraints and base-manipulator …
flying space robots. To solve the two challenges of task constraints and base-manipulator …
Reinforcement learning for soft sensor design through autonomous cross-domain data selection
Data-driven soft sensors have been extensively applied in the process industry for quality
variable estimation. It is challenging to build reliable soft sensors for complex industrial …
variable estimation. It is challenging to build reliable soft sensors for complex industrial …
A two-stage bayesian optimisation for automatic tuning of an unscented kalman filter for vehicle sideslip angle estimation
This paper presents a novel methodology to auto-tune an Unscented Kalman Filter (UKF). It
involves using a Two-Stage Bayesian Optimisation (TSBO), based on a t-Student Process to …
involves using a Two-Stage Bayesian Optimisation (TSBO), based on a t-Student Process to …
HMM based adaptive kalman filter for orientation estimation
P Li, WA Zhang, JH Zhang - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
An adaptive orientation estimation method based on hidden Markov model (HMM) using
multiple Magnetic Angular Rate Gravity (MARG) sensor is proposed to address the problem …
multiple Magnetic Angular Rate Gravity (MARG) sensor is proposed to address the problem …
Robust adaptive smooth variable structure Kalman filter for spacecraft attitude estimation
R Liu, M Liu, G Duan, X Cao - Aerospace Science and Technology, 2024 - Elsevier
This paper proposes a novel robust adaptive filter that combines smooth variable structure
filter and extended Kalman filter for the spacecraft attitude estimation with model uncertainty …
filter and extended Kalman filter for the spacecraft attitude estimation with model uncertainty …
Roll and Pitch Estimation From IMU Data Using an LPV H∞ Filter
Fusion schemes used for estimating roll and pitch angles from inertial measurement unit
(IMU) data typically suffer from one or more of the following limitations: sensitivity to …
(IMU) data typically suffer from one or more of the following limitations: sensitivity to …