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 synchronise data for fusion in Kalman from multiple sensors with different timestamp information?

I'm using Kalman filter to track the position of a vehicle and receive position data from 2 sensors: A GPS sensor and an Ultrasonic sensor for which I want to implement sensor fusion into the Kalman. ...
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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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How do Particle Filters give estimates of uncertainty?

In the Kalman Filter the final covariance matrix is the estimate of the filter's uncertainty. How does one do so in Particle filters? Is it just the variance among the particles for each state? If so, ...
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Sensor fusion of GNSS and IMU using UKF

I do have a land-based robot with an IMU and a GNSS receiver. From the IMU, I get the velocity and acceleration in both $x$ and $y$ directions. From the GNSS receiver, I get the latitude and ...
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Is Kalman filter really desired here?

I am trying to use Kalman Filter in my project to eliminate outliers that go beyond certain limit. I am use 1D lidar to get the distance between the robot and an object. I get pretty accurate values ...
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Is the covariance matrix in the extended Kalman filter guaranteed to be positive definite (ignoring numerical errors)?

I understand that due to numerical errors (e.g., round off error and machine precision) that the covariance matrix may not be positive definite, but if computers had infinite precision, is the ...
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Not getting expected performance from kalman filter+mahalanobis distance

I am using a 1D lidar in one of my projects and it returns the distance it measures, in millimeters (mm). At some point in time, it gives garbage values that go as high as 10,000 or higher, when the ...
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309 views

How to model transition matrix in indirect kalman filter with external orientation estimate

I am trying to implement an indirect/error state kalman filter following Quaternion kinematics for the error-state Kalman filter. However, instead of modelling the orientation and error in orientation ...
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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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Quadcopter sensor fusion

I'm interested in quadcopter position tracking using a mix of IMU and visual navigation. I want to implement an EKF filter but what's not clear to me is how the filter would be updated using the ...
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276 views

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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EKF SLAM : SLAM specific Jacobians for new landmarks

I am currently trying to understand the books SLAM for dummies and Simulataneous localization and mapping with the extended Kalman filter to implement slam. I have understood steps 1 and 2 SLAM for ...
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211 views

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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IMU Vision Fusion using EKF

I am trying to track an object indoors using an IMU (only accel and gyroscope) and a visual marker. This is similar to IMU+GPS fusion, where GPS is effectively replaced by the position that my vision ...
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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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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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63 views

2D Visual-Inertial Extended Kalman Filter

I am trying to implement an Extended Kalman filtering for combining IMU data and visual odometry in a simple 2D case where I have a robot that that can only accelerate in its local forward direction ...
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UKF for radar implementation

I'm struggling to implement Unscented Kalman Filter for tracking objects using radar. My state vector contains [x y z vx vy vz] and I can measure [rho phi theta velocity]. So everything looks trivial ...
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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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Bias correction for multiple sensor fusion through Kalman Filtering

I am learning Kalman Filters and was working on a simple example: Temperature measurement of a room by using 4 thermometers(different biases and noises) if i consider that there is no bias in the ...
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State propagation from uncertain control input

Consider a nonlinear system $x(k+1)=f(x(k),u(k))$, where $x(k)\in\mathbb{R}^{n}$ is the state, $u(k)\in\mathbb{R}^m$ is the control input. Here $u(k)$ is normally distributed RV with mean $\mu_u(k)$ ...
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Kalman Filter for 2d pose

I'm really sorry if this is a dumb question, but I don't have a clue on how to do this. I'm trying to write a kalman filter with a State vector of : {x, y, ẋ, ẏ, ẍ, ÿ } To estimate the 2 dimensional ...
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Regarding kalman filter implementation

I think I might have originally posted this in the wrong stack exchange forum, link. I think this might be the right place, I am not sure if posting again is considered "bad style", I apologize if ...
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Custom implementation of robot_localization package

I plan to implement a sensor fusion of IMU + Visual odometry using an EKF. I came across the excellent robot_localization package which does pretty much all that I want. However, I need to use perform ...
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285 views

Convert Vehicle coordinates to World coordinates for positioning

I'm tracking the position of a vehicle along a certain trajectory using the Kalman filter and the idea is to check for improvements in position estimation through fusion of data from multiple sensors (...
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Kalman filter with missing dimension on measurement input

I am exploring the option of using a EKF with my differential drive robot. I do not have any prior experience with kalman filters. The robot that is under consideration has two wheel encoders for ...
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How do you handle angle discontinuities in estimation problems?

When one is implementing a state estimator in a system that involves kinematics, will inevitably face the problem of angle discontinuities, i.e., the fact that the angles have to be wrapped between ...
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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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285 views

What are wheel ticks and wheel impulses?

I'm tracking the position of a vehicle along a certain trajectory using the Kalman filter and we have odometry data provided to us which gives the x-position of the vehicle, y-position of the vehicle ...
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646 views

Reducing noise between 3 ultrasonic sensors and make Autonomous Robot more precise

I made an autonomous robot with 3 ultrasonic sensors. I want to reduce the noise between the 3 sensors and make it gradually slow when it approaches an obstacle. My code is mentioned below. Please ...
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Where do matrix A and A transpose come from in calculating the predicted covariance matrix?

I don't understand where the matrices A and A transpose come from in the equation in this series. I have done a one-dimensional ...
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Unscented Kalman Filter for Dummies

I need some help here because I can't figure how the Unscented Kalman Filter works. I've searched for examples but all of them are too hard to understand. Please someone can explain how it works step ...
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Difference between observed errors and this error matrix in kalman filter?

I have been watching this video series to try to understand the kalman filter. The instructor has this layout explaining the process. What I don't understand is the difference in the error matrix <...
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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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EKF sensor fusion

What is the standard way to fuse multiple sensor measurements in an EKF framework? Say you have Odometry, IMU and some form of Lidar which can produce landmarks. EKF is normally presented as a ...
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EKF-SLAM what should the observation model be?

I am implementing an EKF algorithm for a drone localization, and while I was defining the observation model I got a bit confused. This is my situation: I have a drone which is able to give me the ...
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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 ...
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Kalman filter with a known motion model

I have a robot whose pose $(x, y)$ is defined relative to the global frame. I have a sensor which estimates the robot's current pose in the global frame, and the sensor is known to have Gaussian error....
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31 views

Uncertainty in grid based fastslam

Given I am building a grid map, and poses are represented using particles, how can I calculate the uncertainty of a pose In a grid based fastslam 2.0?
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How can i fusion gyroscope and accelerometer when accelerometer has only roll,pitch val?

I'm currently studying IMU Sensor with 6dof(gyro and accelerometer). My goal is to get Orientation of robot, and i found out that only 6dof imu sensor wouldn't be possible to get a correct Orientation ...
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Can someone help me understanding reference frames in OxTS data in KITTI Vision Benchmark dataset?

If anyone has worked with KITTI dataset, can you explain the reference frame used in roll pitch yaw values? I downloaded the raw data from this link: http://www.cvlibs.net/datasets/kitti/raw_data.php ...
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what kind of processing is required on raw IMU data before it is fed into a filter?

Im working on quadcopter. At this stage im coding a reference system for quadcopter using 10DOF board.At this stage im at the point of only getting raw data values from accelerometer, gyroscope, & ...
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How to calculate encoders odometry covariance

I am currently working on ROS based autonomous skid steered robot . as I have seen in the literature the base controller needs to subscribe to the geometry_msgs/cmd_vel topic output by the move_base ...
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Advantage of Kalman filter in differential drive planar robot

We need to estimate the position and orientation of differential drive robot by using encoders and imu sensor. For this specific case, is there any advantage of using Kalman filter than taking the ...
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EKF landmark-based help needed

I am new in localization algorithms and EKF is new for me as well. I think that I implemented EKF (the whole code of class is here. I have problems in updating bearing angle of the robot. Basically I ...
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Transforming between a local and global frame for a Kalman filter

I want to track an object in a global Cartesian frame, denoted $G$. The object has a local frame, denoted $L$. The object is controlled by a velocity command $v$, defined in its local frame. This "...
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58 views

Where to include velocity in a Kalman filter

I am trying to understand some of the basics of the Kalman filter. The problem I am working on is quite complex, but I have spent some time trying to simplify the problem with an example. So, let's ...
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487 views

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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60 views

Some Kalman filter implementation queries

Just to clear some doubts: Qn 1. Does kalman filter require constant time step? From my own study, it does not seem necessary to have a constant time step. You just need to take into account time ...
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State-dependent Covariance in the Kalman Filter

When using a Kalman filter, one of the variables that must be defined is a matrix representing the covariance of the observation noise. In the implementations I have seen, this matrix is defined once, ...

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