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When multiple miniature vehicles with individual position and inter-vehicle distance measurement ability collaborate in a formation, navigation base can be established by data fusion in a decentralized and standalone scheme. A Composite Data Fusion (CDF) algorithm which combines Least Square Error and Kalman Filtering is proposed in this paper to build navigation base with optimized computing stress...
Precision of vehicle navigation can be significantly improved by adding motion constraints. How to model multi-motion constraints and choose appropriate motion constraint according to vehicle mobility need to be solved in practical usage. This article established a unified state error model and deduced a measurement model for several common vehicle motion constraints, like ZUPT, MCA and HDR, used...
In this paper, a fusion CKF algorithm with TDRS (Tracking and Data Relay Satellite) and ground stations is presented for a micro reentering USV (Unmanned Space Vehicle). A micro reentering USV has high lift-drag ratio and maneuverability, unlike traditional reentry vehicle, is hard to track. In order to solve this problem, a fusion strategy of CKF (Cubature Kalman Filter) with multi-sensors is estimated...
An integrated navigation method of strapdown inertial navigation system(SINS) and odometer basing on Kalman filter was introduced. In the integrated navigation, error of SINS, inertial measurement unit(IMU) and odometer could be estimated and compensated online. Based on the integrated navigation measurement equation, together with the combining typical maneuver of land vehicle and error propagating...
This paper presents a new continuous-time Kalman-like filter directly on SO(3) for attitude estimation of a vehicle with vector and gyro measurements. The presented filter is inspired by a recently developed norm-constrained Kalman-like filter, which has successfully been applied to the attitude estimation problem when a quaternion parameterization is used. The filter is compared with a continuous-time...
This paper presents the Optimized Kalman Particle Swarm (OKPS) filter. This filter is a new robust data fusion approach adapted for ego-vehicle localization in degraded signal conditions. The OKPS is the improved version of the hybridization of the Particle Filter (PF) by Particle Swarm Optimization notions (PSO). Taking also some features from the Extended Kalman filter (EKF), the OKPS is designed...
This paper implements an interval Kalman filter (IKF) for the navigation of the Springer uninhabited surface vehicle. Interval filters become necessary when the system dynamics are not known precisely or vary unpredictably, but can nevertheless be described in terms of bounded intervals. Such filters based on interval systems require the use of interval arithmetic (IA) for their operation. One of...
A ground-truth environment for mobile robot localization is developed. The sequential update extended Kalman filter is employed to fuse data from a Sick Nav200 laser positioning system and multiple onboard sensors to provide highly accurate robot pose estimation. Results are suitable for validation of mapping, localization and kino-dynamic modeling. Experimental work presented covers odometry calibration...
Attitude estimation for an aerial vehicle using the Kalman Filter - KF- with experimental validation is presented in this paper. The data fusion is made using simplified representations of the kinematics of the aerial vehicle and the accelerometer measurement model. The resulting algorithm is computationally efficient as it can be run at up to 500 Hz on a low-cost microcontroller. The observer is...
This paper demonstrates that the vehicle sideslip can be estimated through the kinematic relationship of velocity measurements from two low-cost GPS receivers. To compensate for the low update rate of low-cost GPS receivers, acceleration/angular rate measurements from an inertial measurement unit (IMU) are merged with the GPS measurements using an extended Kalman filter (EKF). Two technical challenges...
In this paper we present a method for prediction and trajectory tracking of a set of vehicles operating in a port. The objective is to enable the prediction of risk situations in order to avoid collisions. The system is designed for high traffic areas located in ports or civil engineering projects, environments in which traffic occurs without structured lanes of movement. While many studies have been...
Standard extended Kalman filtering algorithm usually needs a little precise initial value, but Strap down inertial navigation system(SINS) coarse alignment precision for marching vehicle can't meet the requirement. So UKF (unscented kalman filter) was proposed to achieve SINS initial alignment for marching vehicle with odometer aiding. The state equation for large misalignment error model was expounded,...
Many mechanical systems that suffer from non-holonomic constraints have attracted a lot of attention recently due to the theorem of Brockett. One such system is a wheeled mobile robot (WMR). Equipped with a proper sensors the robot has an advantage over a human since it can easily maneuver in dangerous environments, and could be rapidly modified or improved to fulfill any specific tasks. Thereby,...
This paper considers the application of feature-based simultaneous localisation and mapping (SLAM) using a random finite sets (RFS) framework for an autonomous underwater vehicle. SLAM allows for reduction in localisation error by tracking features which provide a fixed external reference. The SLAM problem is addressed here using a single-cluster probability hypothesis density (PHD) filter. The filter...
As a distributed parameter system, traffic flow model of freeway traffic is determined by the traffic state on-road and boundary flows form on-ramp or off-ramp sections. The existing studies for traffic estimation mainly focus on the traffic parameter, namely density (or vehicles) of mainline traffic. In this paper, Kalman filtering for simultaneous traffic counts and off-ramp flow estimation is proposed...
Driver assistance systems such as automatic steering for lane keeping are of particular importance for vehicle's lateral safety, and onboard look-ahead cameras are widely employed to acquire surrounding information for realization of such applications. In fact, vision-based lane keeping and automatic steering have been intensively studied in the past few decades. Meanwhile, electric vehicles, as green...
This paper describes the estimation of the unmeasurable variables that are needed for controlling an unmanned aerial vehicle during a flight or for developing control strategies. During these processes, not all the necessary variables can be measured directly by the sensors on board. Some of them need to be estimated or calculated using other measurable variables and numerical calculus.
Various reliable UDP with flow control schemes have been widely adopted to enhance the native UDP protocol. However, all existing schemes exhibit one or more drawbacks that prevent them from achieving the optimal performance in practice. For example, some schemes under-utilize the available bandwidth; some schemes enforce high overhead logic; and some schemes have rigid policies and parameters that...
When multiple miniature vehicles with inter-vehicle distance measurement ability collaborate in a formation, navigation base can be established without external assisting systems. Shared navigation data is fused to compensate the drift of navigation system and the noise from distance measurement. Existing algorithms like Least Squared Error (LSE) can process nonlinear measurements at high speed, but...
The alignment of inertial navigation system (INS) body axis with vehicle body frame (VBF), and calibration of odometer's scale factor are vital necessities for INS/Odometer integrated system. The application of nonholonomic constraints and odometer outputs require the INS body frame be well-aligned with VBF, any misaligned attitude angles will cause serious degradation in position drift errors and...
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