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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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Sensorfusion of odometry, accelerometer and gyroscope using Indirect Kalman Filter

I'm trying to implement an indirect Kalman for pose estimation of a wheeled robot. I found two papers that describe this approach. CMU. Journal (2006) Vol. 5(1) IFAC Conference on Embedded Systems ...
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IMU and encoder fusion

I'm trying to simulate data fusion for a 4-wheeled mobile robot using ekf and am using IMU and wheel encoders as sensors,where IMU measures linear acceleration and angular velocity and encoder ...
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Why is the Kalman filter a filter and not a control system?

Why is the Kalman filter a filter and not a control system? The Kalman filter is a recursive filter which can be used to estimate the internal state of a linear dynamic system with noise in the signal(...
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Navigation - GPS + IMU; how to make it more accurate?

Currently, I am trying to navigate a small robot car to point A from my current position. The car has a GPS sensor and a BNO055 IMU(Gyro + Mag + Acc). I know the GPS co-ordinates of point A. Using the ...
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How to find Q and R in the Kalman filter according to known noise information?

My team built this linearized model in Simulink which works pretty well. I am currently building a continuous kalman filter. I assume some noise disturbance in the input and the measurement like what ...
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Kalman filter to fuse ultrasonic altitude sensor and accelerometer

I'm a little confused on how to set up the Kalman filter matrices to fuse an ultrasonic altitude sensor and accelerometer from IMU. I am trying to implement this for a quadcopter. And what I'm ...
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How is the GPS fused with IMU in a kalman filter?

I've been trying to understand how a Kalman filter used in navigation without much success, my questions are: The gps outputs latitude, longitude and velocity. While the IMU outputs acceleration and ...
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How to accurately navigate from one GPS coordinate to another using just GPS & IMU? [duplicate]

I'm looking for ways to accurately navigate from one GPS location to another. I have a GPS sensor and an IMU. I can calculate the distance with the help of GPS I believe and with the help of ...
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Sensor fusion to calculate joint angles between segments of a robot arm using IMU data

I have an IMU attached to each of the segments of a robotic arm, which gives me accelerometer and gyroscope data. My goal is to first of all improve the quality of the sensor readings and subsequently ...
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Fusing absolute robot localization from markers

I have a system which is composed of a rig of 8 cameras which are used for detecting markers in the environment and which outputs 8 estimates of the absolute robot's position and orientation. Now, I ...
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Problem with UKF weights when calculating predicted state

I'm having troubles implementing a UKF during the calculation of $\overline{\mu_t}$, specifically in this step: $$\overline{\mu_t} = \sum_{i=0}^{2n}w_m^{[i]}\chi_t^{*[i]}$$ My problem I'm facing is ...
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State-vector for distance measurement between two autonomous cars

I hope someone can help me: Given two autonomously driving cars, I want to make sure they keep a constant distance to each other. For this purpose, I want to design a Kalmanfilter. Typically, the ...
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Fixed-Delay Kalman smoother with/without augmented measurements

There are several algorithms regarding fixed-lag Kalman smoothing. In most cases, an augmented state vector is defined in which the elements are the current and delays of the original state vector. ...
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How to determine the Process- and Measurement Noise Covariance Matrix of a Kalman Filter

I'm stuck with the following problem: In a Kalman Filter, we assume the following holds: The state vector can be filled with values which are returned by actual sensors. The Transition matrix needs ...
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How can I determine the Transition Matrix of a Kalman-Filter ?

I am trying to set up a Kalman-Filter to filter position-measurements of a self-driving car. To do so, I consider a state-vector with 5 elements and am now trying to set up the Transition Matrix. As ...
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Kalman-Filter: how to solve angles near +/-pi?

I'm trying to get into Kalman filters. I've noticed an issue with Euler angles near -180°/180° (or -pi/pi) and wonder how to correctly resolve this. Its often said you need to normalize the angles ...
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Sensor fusion - Kalman for two identical position sensors

I require a little help in the implementation of my filter. I am currently working with two Leapmotion devices for the physiological study of hand vibrations. For this we call each of the devices "L ...
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Doubts in the implementation of a Kalman filter to merge position data from two identical sensor

I'm currently working on the implementation of a system for calculating the vibrations of a hand using two Leapmotion devices, these devices deliver in real time the spatial location (x,y,z) and the ...
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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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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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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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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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167 views

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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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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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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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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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 ...