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Questions tagged [kalman-filter]

A Kalman filter is an optimal estimator for linear dynamical systems with Gaussian noise. Extensions to non-linear systems are included through the Extended KF and Unscented KF.

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How to add a magnetometer in an Extended Kalman filter for innovation update?

I can't find out the response so I am posting here. My post kind of follow this one : Adding magnetic field vector to a Kalman filter but I already know that I don't have to put the magnetometer in a ...
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robot localization with start and end positions known to be the same

I've a robot that starting at a point moves certain distance and comes back to the start location. I've used the methodology explained here to localize the robot as shown in the below picture. ...
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Why information filter called information filter

We all know Information Filter is a dual representation of kalman filter. The main difference between information filter and kalman filter is the way the Gaussian belief is represented. In kalman ...
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Position Estimates from sensor fusion

I have a quadcopter, and several components in play. First, I have a real position system (VICON), and I also have a SLAM platform. Then, of course, the IMU on the quadcoptor. I am trying to ...
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the biases in the state vector of extended kalman filter(EKF)

I am reading one paper on observability Observability Analysis of Aided INS with Heterogeneous Features of Points, Lines and Planes. The state vector contains the current IMU state and the feature ...
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How to implement Kalman to merge the data obtained by two Leap Motion devices?

Only position data is obtained from Leap Motion devices. This data was already processed to be on the same coordinate axis by means of a homogeneous transformation. I'm reviewing WTF is Sensor ...
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Kalman filter with measurements indirectly determining state

I have a question regarding a 'fundamental' understanding of the Kalman filter. So, for my application I'm trying to estimate state $x = [\theta~\dot{\theta}~\ddot{\theta}]$ of a robot based on ...
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Alternate perspective other than probabilistic perspective to implement slam

I am bother on some line which is written is Probabilistic Robotics book by Dr.Sebestian Thrun From a probabilistic perspective, there are two main forms of the SLAM problem,which are both of equal ...
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Position Tracking using IMU

I am working on a robot tracking application, where our main tool (a camera) for locating the x & y position of the robot is working on a quite low frequency. Therefore, I am looking for ways to ...
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Stationary Kalman Filter Speed Estimation

I try to implement a Kalman Filter for speed estimation with a rotary encoder. What I can measure ist the absolute position and I try to estimate the angular velocity. A paper I found is the ...
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Lost on SEIF Slam repeated update landmark

I am working on Sparse Extended Information Slam. I take the reference from Probabilistic Robotics, by Dr.Sebastian Thrun (Chapter 12,page 303). I have some doubt about the implementation of the ...
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SEIF slam: Effect on information matrix when there is no landmarks

I studied about Sparse Extended Information Filter slam. I want to clarify some points regarding this topic. As per the sparse extended information(SEIIF) slam when the robot sees some landmarks it ...
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SEIF ,online version of Graph slam create doubt in Motion Update state

I have a thesis work about Graph Slam The GraphSLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures I try to implement it with the help of this paper but during the ...
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How should I understand sequential importance resampling in a particle filter?

Suppose I implement a particle filter with $n$ particles. This is a brief description of my understanding of a particle filter. For the first step, I throw out $n$ particles some distance from my ...
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Robot localization using sensor fusion (How to model the Extended Kalman Filter)?

I am new to the robotics field and sensor fusion as well. I am trying to localize my robot using the data from my camera and the odometery through extended Kalman filter. I have the data offline, I ...
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Graph Slam Landmark remove and then again add it

I try to implement Graph Slam in real dataset. My data set have some data that describe that the Robot observe same landmark over and over with a large amount of time difference. Prof. Sebastian ...
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How to detect loop in robot movement observing odometer data

I have some odometer data. This data are based upon robot movement. I can transfer those raw data to a motion equation from where I get x,y,and theta co-ordinate of a Robot. If I plot those x,y ...
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How exactly does sensor fusion work in Kalman filters?

I've been looking into implementations of Extended Kalman filters over the past few days and I'm struggling with the concept of "sensor fusion". Take the fusion of a GPS/IMU combination for example, ...
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How to apply Kalman filter in this case?

I have some straight and curve pieces with numbers, they are used to build tracks (of $5$ lanes) for my cars (figure $1$), I can send commands to the cars using an SDK on the Raspberry (set the speed ...
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GPS + IMU fusion frame without magnetometer

I am trying to implement the Kalman filter for GPS + IMU fusion. I have the position and velocity (at a low rate) from the GPS module. I further have the accelerometer and gyroscope output in the IMU ...
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Range Only Kalman Filter

My question concerns the proper way to implement a Kalman Filter using range only information for localization. Imagine I have a robot moving within an environment and over time he receives some range ...
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Kalman filter and ekf main difference in elaborate way

I am studying about various filtering techniques for Robot pose esitimation. I came to know two very well known filter technique Kalman Filter and Extended Kalman Filter. To know about this two ...
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Position-Attitude Kalman filter with Quaternions

I want to design an EKF to estimate the position of a UAV. If I were doing this with Euler angles then I would have a state vector that would look like \begin{bmatrix}north&east&down&...
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Tracking vehicle 6 states extended kalman filter required?

I'm trying to track an accelerating vehicle using a camera, an IMU, and a GPS. I use for the state space equation a constant acceleration model: The states are the position, the velocity, and the ...
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KF/ EKF - Modelling and tuning noise matrices and other parameters

I am developing C++ code to estimate roll and pitch of a camera using accelerometer and gyroscope. The roll, pitch and yaw are in my state space ($X_t$) and the process is modeled as: $\bar{X_t} = X_{...
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How to convert/transform robot local frame to global frame to use in Kalman Filter?

I'm currently working on the iRobot Create 2 platform using a RaspberryPi (Python) and ROS. I have an indoor navigation/ GPS system, which can provide me with x,y coordinates within its coordinate ...
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Orientation estimation using gyro and accelerometer when sensor platform has high acceleration

I am trying to estimate the orientation of a sensor platform using gyroscope and accelerometer. I am using a Kalman filter based approach. I integrate the readings ...
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IMU GPS integration (full state implementation)

Hi all, I'm trying to implement 'total state IMU/GPS Kalman filer' The state will be not the error state, but the total state: [attitude, velocity, position, accel bias, gyro bias]. Can anyone help ...
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The final step in kalman filter to correct/update the covariance matrix

I see that, in the correction step of Kalman filter, there is an equation to update the covariance matrix. I have been using it in the form: P = (I - KH)P' Here ...
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Kalman filter for slow ground vehicle with RTK

I have been using dual RTK receivers for my tractor projects. This gives me reliable position, heading, and tilt at low rates (10 Hz). I recently began working with an INS (an Advanced Navigation ...
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Transforming an inverse covariance matrix

I have a linear map, $J$, from one space to another. I can transform a covariance matrix, $P$, from one space to another by using: $P' = JPJ^{T}$ However, in my situation I have an inverse ...
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Kinematic Kalman filter and state estimation of a robot without wheels

I have a question about the Kalman filter for state estimation, I'm working on the state estimation of a robot, I should be able of tracking its position, my tutor recommended me to make an estimate ...
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Rotation composition When using Kalman Filter

I am implementing a Kalman Filter for the following situation. I have a camera set in a room that can detect the position and orientation of a marker (ARUCO) in the room. Therefore I have the ...
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Sensor fusion under unknown correlations: can covariance intersection account for delays?

Of late, there has been some interest in cooperative estimation algorithms in robotics, where the information sources are usually sensors such as cameras. When multiple robots observe surrounding ...
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Delayed Kalman navigation based on two way ranges

I am interested to know the basic principle of the "Delayed KF" when considering an underwater robot aiming to localize it self using a LBL system. More practically, in order to calculate the ...
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Why does a Bayesian Filter require random controls?

As stated in Probabalistic Robotics, the proof for correctness of a Bayesian Filter relies on the fact that $$p(x_{t-1}|z_{1:t-1},\ u_{1:t}) = p(x_{t-1}|z_{1:t-1},\ u_{1:t-1})$$ In order to justify ...
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Robot heading uncertainty values

I'm tracking the state of a robot using an EKF defined by: $$(x,y,\theta)$$ where $x$ and $y$ are the coordinates in the ground-plane and $\theta$ the heading angle. I initialized the covariance ...
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Jacobian of kinematic IMU Model

I have the following problem: given two Input Vectors $x = \begin{pmatrix}x\\y\\z\\v_x\\v_y\\v_z\\q_1\\q_2\\q_3\\q_4\end{pmatrix}$, $u = \begin{pmatrix}a_x\\a_y\\a_z\\w_x\\w_y\\w_z\end{pmatrix}$ time $...
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Prediction step for EKF based localization

In my current problem, I'm supposed to use the Extended Kalman filter to localize my diffrential drive robot that uses encoders and laser scanner to traverse the area. During the prediction step, ...
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State prediction of vehicle with Ackermann steering geometry using Kalman-Filter

I am trying to have a Kalman-Filter (or Extended-KF) give me positions for a small remotely controlled vehicle with an Ackermann steering geometry (moving on a plane surface). The control commands I ...
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Measurement model for Kalman filter but non-zero mean

I'm fusing two vision-based algorithms using the Kalman filter to estimate the state of a vehicle $X=(x,y,\theta)$ where $x$ and $y$ are the coordinates in the plan and $\theta$ the heading. The ...
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Meaurement function model in kalman filter

I'm tracking the state of a vehicle using kalman filter. The state is represented by 3 random variables: $X=(x,y,\theta)$ where $x$ and $y$ refer to the position in the plan and $\theta$ to the ...
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How to compute the observation matrix for a Kalman Filter?

If my state vector is just a representation of the error state of a quaternion represented as $[\delta \bf{q} ]$ which is a 3x1 vector and my external update is from an accelerometer, how would I ...
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how to sync the timer in control system with ROS?

To simulate a system, a global timer will be set and all submodules will be synchronized with that timer to work together. such as PID controller, kalman filter, PWM module etc. How do you sync the ...
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Kalman filter for vision based pose estimation: 'good' measurements not improving system covariance

I am starting off with a very simple Kalman filter for vision based pose estimation (PnP algorithm). The filter is inspired by the constant velocity model in this OpenCV tutorial, but I am ignoring ...
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Industrial Controllers - Why not adaptive control and robust control

This is a question I have thinked about under a very long time. What are industrial controllers? From research I found that PID is the most used in the industry. PID controllers are included in ...
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Unscented Kalman Filter VS Extended Kalman Filter on stability

The Extended Kalman filter is more or less a mathematical "hack" that allows you to apply these techniques to mildly nonlinear systems. The problem with Extended Kalman Filter is if I initialize the ...
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396 views

Standard deviation calculation for a single measurement

I have a robot that takes a measurement of its current pose in the form $$ z = \begin{bmatrix} x\\ y\\ \theta \end{bmatrix} $$ $x$ and $y$ are the coordinates in $XY$ plane et $\theta$ the heading ...
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I fused a GPS and IMU and I am wondering if my results make sense

I am trying to fuse a ublox M8 (https://www.u-blox.com/sites/default/files/products/documents/u-blox8-M8_ReceiverDescrProtSpec_(UBX-13003221)_Public.pdf) with a MicroStrain IMU (http://www.microstrain....
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Calculating the covariance matrix of a measurement

I want to estimate the covariance matrix of a measurement for a robot evolving on plane and having the following state vector. $$ X = \begin{bmatrix} x\\ y\\ \theta \end{bmatrix} $$ $x$ and $y$ are ...