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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Why do I need a Kalman filter?

I am designing an unmanned aerial vehicle, which will include several types of sensors: 3-axis accelerometer 3-axis gyroscope 3-axis magnetometer horizon sensor GPS downward facing ultrasound. A ...
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33 votes
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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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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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3 answers
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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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Kalman Filter GPS + IMU

I know this probably has been asked a thousand times but I'm trying to integrate a GPS + Imu (which has a gyro, acc, and magnetometer) with an Extended kalman filter to get a better localization in my ...
aram's user avatar
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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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What are good methods for tuning the process noise on Kalman filters?

Most often tuning the Kalman filter noise matrices is done by trial and error or domain knowledge. Are there more principled ways for tuning all the Kalman filter parameters?
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16 votes
3 answers
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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 ...
zSt's user avatar
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Open source implementations for GPS+IMU sensor fusion?

Are there any Open source implementations of GPS+IMU sensor fusion (loosely coupled; i.e. using GPS module output and 9 degree of freedom IMU sensors)? -- kalman filtering based or otherwise. I did ...
O.K.'s user avatar
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10 votes
1 answer
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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 ...
automatom's user avatar
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9 votes
1 answer
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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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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 ...
Sibbs Gambling's user avatar
7 votes
3 answers
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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 ...
josh131's user avatar
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7 votes
2 answers
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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 ...
josh131's user avatar
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6 votes
2 answers
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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 ...
CroCo's user avatar
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Are there off the shelf solutions for GPS+INS (accelerometer,gyro,magneto) sensor fusion for getting filtered/fused location and speed output?

I am working on a project that needs tracking location and speed of pedestrians/runners/athletes (so not really robotics, but I see a lot of related usage and posts in the robotics domain, and an ...
O.K.'s user avatar
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3 votes
1 answer
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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 ...
gondsieg's user avatar
3 votes
1 answer
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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 ...
numberCruncher's user avatar
3 votes
1 answer
210 views

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 ...
Encipher's user avatar
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3 votes
2 answers
269 views

Kalman filter prediction questions [closed]

I have a dataset where measurements were taken at 1 Hz, and I am trying to use a Kalman filter to add predicted samples in between the measurements, so that my output is at 10 Hz. I have it ...
anti's user avatar
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2 votes
1 answer
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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 ...
Encipher's user avatar
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2 votes
1 answer
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cartesian velocity control loop implementation

I'm using ROS (noetic) to intuitively control a franka manipulator using the panda_robot package for the simulation. I've set up an extended kalman filter which fuses the following measures: IMU data:...
dcfg's user avatar
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1 answer
776 views

Adding magnetic field vector to a Kalman filter

I currently have an error state Kalman filter with the state vector $(p, v, q, \omega, a, g)$ where $q$ is the quaternion orientation. I would like to add the information coming from a magnetometer to ...
Nopestradamus's user avatar