# 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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### Open source implementations of EKF for 6D pose esimation

I am looking for open source implementations of an EKF for 6D pose estimation (Inertial Navigation System) using at minimum an IMU (accelerometer, gyroscope) + absolute position (or pose) sensor. ...
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### How to estimate yaw angle from tri-axis accelerometer and gyroscope

I would like to estimate the yaw angle from accelerometer and gyroscope data. For roll and pitch estimate I've used the following trigonometric equations: ...
285 views

### Ensemble Kalman Filter SLAM

I know that there is an extended kalman filter approach to simultaneous localization and mapping. I'm curious if there is a SLAM algorithm that exploits the ensemble kalman filter. A citation would ...
944 views

### Kalman filter Issue - GPS Odometry Fusion

I am working on estimating a robots pose using Odometry and GPS. My first problem is that all kinematic model i have seen for a differential drive robot proposes using the displacement of the left ...
144 views

### Observation Model Jacobian for Fixed Transforms

Let's say I have a hypothetical sensor that provides, for example, velocity estimates, and I affix that sensor at some non-zero rotational offset from the robot's base. I also have an EKF that is ...
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### Why should I still use EKF instead of UKF?

The Unscented Kalman Filter is a variant of the Extended Kalman Filter which uses a different linearization relying on transforming a set of "Sigma Points" instead of first-order Taylor series ...
7k views

### How much should I expect a Kalman filter to converge?

I am learning about Kalman filters, and implementing the examples from the paper Kalman Filter Applications - Cornell University. I have implemented example 2, which models a simple water tank, ...
175 views

### Point tracking from a mobile robot

How can I track a fixed point $P=(x_P, y_P)$ from a moving robot? Coordinates of $P$ are relative to the state/pose of the robot (x axis looks forward the robot and y axis is positive on the right ...
1k views

### Multiple position estimates fusion

I have a system in which I have two separate subsystems for estimating robot positions. First subsystem is composed of 3 cameras which are used for detecting markers the robot is carrying and which ...
957 views

### Kalman Filter when states are not observable at the same time?

I have a system that I can make a strong kinematic model for, but my sensors send readings at unpredictable times. When I say unpredictable, I am not just saying the order the readings will arrive, I ...
2k views

### What is the best way to fuse measurements from IMU, LIDAR, and Encoder information in some recursive bayesian filter?

I am doing SLAM with a four wheeled (2-wheel drive) differential drive robot driving through some hall way. The hallway is not flat everywhere. And the robot turns by spinning in place, then traveling ...
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### How to rotate covariance?

I am working on an EKF and have a question regarding coordinate frame conversion for covariance matrices. Let's say I get some measurement $(x, y, z, roll, pitch, yaw)$ with corresponding 6x6 ...
191 views

### Slam and Vision (good resources)? [closed]

I would like to know if there is a good source that combines Slam problem with vision. From mathematical perspective, there are numerous resources that handle SLAM ,however, I didn't find a good ...
126 views

### Can motion model noise be zero?

Can I assume the noise of motion model to be zero? If so, what are the consequences of doing so?
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### What to do when the control input of the Kalman filter is unknown?

I am implementing a simple Kalman Filter that estimates the heading direction of a robot. The robot is equipped with a compass and a gyroscope. Say at time $t-dt$, the compass reports a reading \$\...
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### How to model unpredictable noise in Kalman Filter?

Background: I am implementing a simple Kalman Filter that estimates the heading direction of a robot. The robot is equipped with a compass and a gyroscope. My Understanding: I am thinking about ...
167 views

### existence probability of an object in fusion

I want to compute an existence probability of an object in a sensor fusion on the high level (having from each sensor list of objects already filtered with e.g. Kalman Filter). There are these ...
487 views

### Is there a benefit to using 2 IMU units on a UAV set at different sensitivities?

I noticed that some IMU units are tuned to be sensitive to small changes, other to large changes and some that can be adjusted between different sensitivities. I am familiar with the use of a Kalman ...
520 views

### object level sensor fusion for multiobject tracking

I want to fuse objects coming from several sensors, with different (sometimes overlapping!) fields of view. Having object lists, how can I determine whether some objects observed by different sensors ...
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### information filter instead of kalman filter approach

I read many sources about kalman filter, yet no about the other approach to filtering, where canonical parametrization instead of moments parametrization is used. What is the difference? Other ...
290 views

### At which stage should filtering be applied to the sensors data?

Shall I filter (kalman/lowpass) after getting the raw values from a sensor or after converting the raw values to a usable data? Does it matter? If so, why? Example: Filter after getting raw values ...
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### Source to learn Kalman Fusion, explanatory code snippets

Currently I am reading a book of Mr. Thrun: Probabilistic Robotics. I find it really helpfull to understand concept of filters, however I would like to see some code in eg. Matlab. Is the book "Kalman ...
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### Taylor Series expansion for EKF

In Probablistic Robotics by S. Thrun, in the first section on the Extended Kalman Filter, it talks about linearizing the process and observation models using first order Taylor expansion. Equation ...
507 views

### Chaining Kalman filters

My team is building a robot to navigate autonomously in an outdoor environment. We recently got a new integrated IMU/GPS sensor which apparently does some extended Kalman filtering on-chip. It gives ...
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### Extended Kalman Filter using odometry motion model

In the prediction step of EKF localization, linearization must be performed and (as mentioned in Probabilistic Robotics [THRUN,BURGARD,FOX] page 206) the Jacobian matrix when using velocity motion ...
221 views

### Can you seed a Kalman filter with a particle filter?

Is there a way of initializing a Kalman filter using a population of particles that belong to the same "cluster"? How can you determine a good estimate for the mean value (compute weighted average ?) ...
780 views

### Noise in motion and measurement models

When using an EKF for SLAM, I often see the motion and measurement models being described as having some noise term. This makes sense to me if you're doing a simulation, where you need to add noise ...
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### EKF-SLAM Update step, Kalman Gain becomes singular

I'm using an EKF for SLAM and I'm having some problem with the update step. I'm getting a warning that K is singular, rcond evaluates to ...
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### How to fuse linear and angular data from sensors?

My team and I are setting up an outdoor robot that has encoders, a commercial-grade IMU, and GPS sensor. The robot has a basic tank drive, so the encoders sufficiently supply ticks from the left and ...
200 views

### What kind of performance can I expect when using an Extended Kalman Filter for calibration and localization?

Currently I have a tricycle style robot that uses an extended kalman filter in order to track 6 state variables. The inputs to the system are a steer encoder, a distance encoder, and a rotating laser ...