In recent years, the error-state Kalman filter (ErKF) has been widely employed in various applications, including robotics, aerospace, and localization. However, incorporating state constraints into the ErKF framework using the estimate projection me...
Attitude estimation has increasingly relied on MEMS inertial measurement units (IMUs) owing to the low cost and miniature size, but the inherent high random noise and error accumulation limit long-term measurement accuracy. This article proposes an i...
This paper investigates the odometry drift problem in differential-drive indoor mobile robots and proposes a multi-sensor fusion approach utilizing a Fuzzy Inference System (FIS) within a Wheel-Inertial-Visual Odometry (WIVO) framework to optimize th...
With the widespread development of multiple sensors for UGVs, the multi-source fusion-navigation system, which overcomes the limitations of the use of a single sensor, is becoming increasingly important in the field of autonomous navigation for UGVs....
The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF) are widely used in underwater multi-sensor fusion applications for localization and navigation. Since these filters are designed by employing first-order Tay...
The accuracy and consistency of error-state Kalman filtering for SINS/GNSS integrated navigation depend critically on properly tuned process and measurement noise covariance matrices. In dynamic operation, these covariances can be non-stationary: ine...
The article addresses the issue of mobile robotic platform positioning in GNSS-denied environments in real-time. The proposed system relies on fusing data from an Inertial Measurement Unit (IMU), magnetometer, and encoders. To get symmetrical error g...
Magnetic pose tracking is a non-contact, accurate, and occlusion-free method that has been increasingly employed to track intra-corporeal medical devices such as endoscopes in computer-assisted medical interventions. In magnetic pose-tracking systems...
Accurate walking trajectory estimation is critical for monitoring activity levels in healthcare and occupational safety applications. Ultra-Wideband (UWB) technology has emerged as a key solution for indoor human activity and trajectory tracking. How...
High-precision positioning is a fundamental requirement for autonomous vehicles. However, the accuracy of single-sensor positioning technology can be compromised in complex scenarios due to inherent limitations. To address this issue, we propose an a...
Foot-mounted inertial navigation is an important option for pedestrian positioning when external localization infrastructure is limited, unavailable, or unreliable. Its performance, however, depends heavily on zero-velocity updates (ZUPTs), which can...
Current multi-modal pose estimation methods often suffer from severe localization divergence and prohibitive computational overhead when confronted with extreme scenarios such as sudden illumination variations, geometric degeneracy, and wheel slippag...
Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, strid...
Low-cost MEMS sensors are widely utilized in UAV platforms to address attitude estimation problems due to their compact size, low power consumption, and cost-effectiveness. Diverse UAV payloads pose new challenges for attitude estimation, such as mag...
GNSS/INS integrated navigation systems play a critical role in marine navigation, providing high-precision position and attitude information for moving platforms. However, in complex marine environments—such as occlusions caused by offshore eng...
Visual inertial odometry (VIO) is the front-end of visual simultaneous localization and mapping (vSLAM) methods and has been actively studied in recent years. In this context, a time-of-flight (ToF) camera, with its high accuracy of depth measurement...
Real-time acquisition of high-precision 3D spatial information is critical for intelligent maintenance of urban infrastructure. While SLAM technology based on LiDAR–IMU sensor fusion has become a core approach for infrastructure monitoring, its...
Bio-inspired tailless flapping-wing micro aerial vehicles (FWMAVs) offer advantages of hovering flight, small size, and high maneuverability, showing potential for confined space missions. Outdoor autonomous flight remains challenging for tailless FW...
Outdoor autonomous mobile robots heavily rely on GPS data for localization. However, GPS data can be erroneous and signals can be interrupted in highly urbanized areas or areas with incomplete satellite coverage, leading to localization deviations. I...
Reliable indoor localization is required for automated guided vehicles (AGVs), robot validation, and industrial digital-twin applications, but ultrasonic positioning can degrade sharply when acoustic visibility changes. This paper evaluates Marvelmin...
Light detection and ranging (LiDAR) is often combined with an inertial measurement unit (IMU) to get the LiDAR inertial odometry (LIO) for robot localization and mapping. In order to apply LIO efficiently and non-specialistically, self-calibration LI...
To regulate the energy flow in orchard ecosystems and maintain the environment, weeding has become a necessary measure for fruit farmers, and the use of automated mowers can help reduce labor costs and improve the economic efficiency of orchards. How...
This study introduces an Enhanced Error-Adaptive Extended-State Kalman Filter Model Predictive Control (EEA-ESKF-MPC) method to tackle strong coupling and inertia in supercritical power plants. By enhancing the ESKF-MPC framework with a mechanism tha...
High−precision and robust localization is critical for intelligent vehicle and transportation systems, while the sensor signal loss or variance could dramatically affect the localization performance. The vehicle localization problem in an envir...
Vision-based navigation systems (VINS) are increasingly utilised as an alternative to GNSS for UAVs operating in urban environments, but they suffer from performance degradation under visual fault conditions like illumination variation, rapid motion,...
In general, the extended Kalman filter (EKF) has a wide range of applications, aiming to minimize symmetric loss function (mean square error) and improve the accuracy and efficiency of state estimation. As the nonlinear model complexity increases, ro...
This paper presents a new set-membership based hybrid Kalman filter (SM-HKF) by combining the Kalman filtering (KF) framework with the set-membership concept for nonlinear state estimation under systematic uncertainty consisted of both stochastic err...
As an important component of autonomous intelligent systems, the research on autonomous positioning algorithms used by UAVs is of great significance. In order to resolve the problem whereby the GNSS signal is interrupted, and the visual sensor lacks...
In networked sensing systems, nonlinear state monitoring and soft sensing are widely used to reconstruct key variables that cannot be directly measured in real time. For such nonlinear estimation tasks, the Extended Kalman Filter (EKF) is a commonly...
In the field of state of charge (SOC) estimation, the Kalman filter has been widely used for many years, although its performance strongly depends on the accuracy of the battery model as well as the noise covariance. The Kalman gain determines the co...
Accurate online parameter identification and state of charge (SOC) estimation are both very crucial for ensuring the operating safety of lithium-ion batteries and usually the former is a base of the latter. To achieve accurate and stable SOC estimati...
The estimation accuracy of the battery state of charge (SOC) directly affects the reliable and stable operation of the battery management system (BMS). In complex operating conditions such as vehicle-mounted applications and energy storage power stat...
In order to attain precise and robust transformation estimation in simultaneous localization and mapping (SLAM) tasks, the integration of multiple sensors has demonstrated effectiveness and significant potential in robotics applications. Our work eme...
As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage o...
This study presents a deep learning–assisted integrated navigation scheme implemented on an autonomous underwater vehicle carrying a Chinese domestically developed strapdown inertial navigation system, designed for operation in surface and litt...
Visual-inertial Navigation Systems (VINS) are nowadays used for robotic or augmented reality applications. They aim to compute the motion of the robot or the pedestrian in an environment that is unknown and does not have specific localization infrast...
High-precision state of charge (SOC) estimation is essential for reliable supercapacitor (SC) energy storage systems. However, irregular noise and sensor biases can degrade estimation accuracy. To address these issues, an estimated-value correction (...
For positioning tasks of mobile robots in indoor environments, the emerging positioning technique based on visual inertial odometry (VIO) is heavily influenced by light and suffers from cumulative errors, which cannot meet the requirements of long-te...
This paper presents the second part of a study aiming at the error state selection in Kalman filters applied to the stationary self-alignment and calibration (SSAC) problem of strapdown inertial navigation systems (SINS). The observability properties...
Nowadays, many precision farming applications rely on the use of GNSS-RTK. However, when it comes to autonomous agricultural vehicles, GNSS cannot be used as a stand-alone system for positioning. To ensure high availability and robustness of the posi...
Sensorless control of synchronous reluctance motors (SynRMs) requires accurate rotor speed and position estimation that is robust to parameter uncertainties and sensor faults. This paper systematically investigates the influence of estimator architec...
Reliable execution of a planned path is essential for autonomous mobile robots and vehicle-like robot platforms. This study experimentally evaluates the path-following performance of a scaled Ackermann-steered autonomous vehicle under different local...
Indoor mobile robots often experience degraded localization accuracy and robustness when relying on a single positioning modality. In addition, conventional pose computation based on Euler-parameterized transformations can be computationally involved...
This paper proposes a cascaded state estimation framework based on proprioception for robots. A generalized-momentum-based Kalman filter (GMKF) estimates the ground reaction forces at the feet through joint torques, which are then input into an error...
In multirotor unmanned aerial vehicle (UAV) GNSS/INS integrated navigation systems, a single filter such as the extended Kalman filter (EKF) or the error-state extended Kalman filter (ESKF) is commonly adopted. However, both methods have inherent per...
Aimed at the problem of small unmanned aerial vehicle (UAV) attitude solution accuracy and real-time performance in short-range navigation flight, in this paper, we propose a fast weakly-coupled double-layer error-state Kalman filter (DL-ESKF) attitu...
Multi-source autonomous navigation-dependable decision making has a crucial impact on the overall performance of navigation systems. To solve the problem of overall system robustness caused by the intelligent-dependable decision making difficulties o...
The compressibility of air, the uncertainty of dynamic models, and the existence of friction make pneumatic servo systems exhibit strong nonlinearity. Furthermore, the confluence of pneumatic-system nonlinearity and interference from the position sys...
We explore the reliability of joint angles in road cycling obtained using inertial measurement units. The considered method relies on 3D accelerometer and gyroscope measurements obtained from two such units, appropriately attached to two adjacent bod...
The application of an ultra-wideband (UWB) positioning system in a Global Positioning System (GPS) denial environment such as an underground coal mine, mainly focuses on position information and rarely involves information such as direction attitude....
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