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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1answer
76 views

Improving Velocity estimation

I have a sensor reduction model which gives me a velocity estimate of a suspension system(velocity 1) . This suspension system estimate velocity is used to calculate another velocity(velocity 2) via ...
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Need of Kalman filters in unimodal measurement model

I have recently been studying Kalman filters. I was wondering that if sensor model of a robot gives a unimodal Gaussian ( as is assumed for LKF) and the environment is pre-mapped, then the sensor ...
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Kalman Filter with incremental encoder + optical mice

Currently I am building a robots with 2 incremental encoders with a optical mice sensor. The reason to install a optical mice sensor is to provide better feedback when slippage happen on the encoders. ...
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Fusion of GNSS position data and prefused 9-dof AHRS data

Bosch, FreeScale, InvenSense, ST and maybe others are releasing 9-dof AHRS platforms containing their own fusion software and outputting filtered/sane/fused data (attitude as quaternion and linear ...
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342 views

Jacobian Matrix of 6DOF Body (with IMU)

I am trying to derive the analytical Jacobian for a system that is essentially the equations of motion of a body (6 degrees of freedom) with gyro and accelerometer measurements. This is part of an ...
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2answers
770 views

differential robot yaw estimation using kalman filter

Hello i am building a differential drive robot which is equipped with quadrature encoders on both of the motors. My aim is to be able to predict the heading (yaw angle) of the robot using a kalman ...
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Ambiguous definition of Error-State (Indirect) Kalman Filter

I am confused by what precisely the term "Indirect Kalman Filter" or "Error-State Kalman Filter" means. The most plausible definition I found is in Maybeck's book [1]: As the name indicates, in ...
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Pose estimation, how to populate set of known edges and points?

I am building an estimator that solves for the camera pose relative to a reference frame which contains a known set of features and edges. Currently, the system works with an unscented kalman filter ...
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595 views

How to choose the state space model for 1 axis gyroscope to implemnt a good kalman filter

I am using this gyroscope in order to measure the rotation of my robot around the z axis. I want to implement a kalman filter in order to improve the values. What i came with since now is this space ...
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Kalman filter model values or state space original value? Which values to use?

I am using L3GD20 and I am trying to implement a kalman filter for it on the stm32f3 discovery board. I have though a few questions about that: After the filter gave me the values, do I have to make ...
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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: ...
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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 ...
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837 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 ...
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1answer
127 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 ...
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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, ...
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163 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 ...
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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 ...
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782 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 ...
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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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3answers
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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 ...
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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 ...
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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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covariance matrix in EKF?

I'm struggling with the concept of covariance matrix. $$ \Sigma = \begin{bmatrix} \sigma_{xx} & \sigma_{xy} & \sigma_{x \theta} \\ \sigma_{yx} & \sigma_{yy} & \sigma_{y \theta} \\ \...
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Explanation of the Kalman Filter [closed]

I am a beginner in robotics, and I am learning about the Kalman filter. I do not seem to get it, though. I am a mathematician, and so it would be helpful if the Kalman filter could be explained in a ...
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What is the Kalman Filter in the basics of its aspects? [closed]

My question is very broad. However I would like a complete description to the very last detail in a way that a foreign exchange student would understand. I want to try my best to master the way the ...
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407 views

Overcorrecting Kalman Filter

I'm trying to get an extended Kalman Filter to work. My System Model is: $ x = \begin{bmatrix} lat \\ long \\ \theta \end{bmatrix}$ where lat and long are latitude and longitude (in degree) and $\...
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Kalman Filter and the state noise vector?

I'm reading Probabilistic Robotics by Thrun. In the Kalman filter section, they state that $$ x_{t} =A_{t}x_{t-1} + B_{t}u_{t} + \epsilon_{t} $$ where $\epsilon_{t}$ is the state noise vector. And ...
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Extended Kalman Filter with Laser Scan + Known Map

I am currently working on a project for school where I need to implement an extended Kalman Filter for a point robot with a laser scanner. The Robot can rotate with 0 degree turn radius and drive ...
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Do I need an accurate flight model for a UAV?

As I understand it, a Kalman filter uses a mathematical model of the robot to predict the robot's state at t+1. It then combines that prediction with information from sensors to get a better sense of ...
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598 views

EKF partial state update question

This is a follow up to Maintaining positive-definite property for covariance in an unscented Kalman filter update ...but it's deserving of its own question, I think. I am processing measurements ...
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Maintaining positive-definite property for covariance in an unscented Kalman filter update

I have an unscented Kalman filter (UKF) that tracks the state of a robot. The state vector has 12 variables. Each time I carry out a prediction step, my transfer function (naturally) acts on the ...
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Jacobian of the observation model? [closed]

The state vector is $$ \textbf{X} = \begin{bmatrix} x \\ y \\ v_{x} \\ v_{y} \end{bmatrix}$$ transition function is $$ \textbf{X}_{k} = f(\textbf{X}_{k-1}, \Delta t) = \begin{cases} x_{k-1} + v_{...
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878 views

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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884 views

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 ...
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1answer
141 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 ...
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475 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 ...
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488 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 ...
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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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997 views

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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937 views

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 ...
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1answer
452 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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3answers
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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 ...
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1answer
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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 ?) ...
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716 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 ...
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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 ...