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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Estimating gyroscope bias for attitude IMU sensor fusion with an unscented Kalman filter
I'm trying to use a UKF as the attitude estimator for a drone with just a gyroscope and accelerometer as sensors. So far, it's going well and after some tuning appears to perform basically as well as ...
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Modeling EKF for localization of an Autonomous Mobile Robot
I've got an EKF for a simple two-wheeled mobile robot, whose states are the pose and the wheel's angular speeds.
I was wondering what were the advantages of having those last two states included ...
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robot_localization GPS causing large drift/covariance spike
I am trying to implement the dual ekf navsat example on my real-world robot. The local EKF with wheel odometry and IMU works quite well and has no issues. As far as I can tell, my global EKF ...
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Odometry into EKF for localization
I want to fuse a Lidar-Odometry into my EKF where I'm already using encoder, IMU, GPS. The odometry has as output a delta pose, how to put that into the filter? How to deal with the covariances?
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Compensate tractor's (vehicle's) tilts in the GNSS-IMU based system
I have the following setup: a tractor with a dual band antenna (from ublox) installed on the vehicle's symmetry axis on the roof (h=3m), approx. 1m ahead of the center of the rear axis (which I ...
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The choice of using quaternions and using gyro & accel separately in EKF
I am working on realising the self-navigation of a vehicle.
I have already written an extended Kalman filter with a state vector using position, velocity, Euler angle, acceleration, and angular ...
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What should I use for a Visual+IMU+GPS fusion? A Madgwick or a Kalman?
I am new to robotics, and recently I am involving in a sensor fusion task using visual input (binocular at present), an IMU, and a GPS module. I have searched for related journal papers for a ...
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Omnidirectional kinematic model in robot_localization's EKF
I am looking for a more detailed mathematical background of robot_localization's kinematic model used for nonlinear kalman filtering.
From the documentation, the ...
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Modelling line sensors for localizing a mobile robot using the Kalman Filter
My goal is to localize a mobile robot with Mecanum wheels in a 8m x 10m area, that is outlined with white lines. The robot weighs around 25 kg, and has a top speed of 2 m/s. The localization should be ...
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How to deal with asynchronous samples in a kalman filter framework multi-sensor fusion?
I have setup a sensor fusion problem to estimate a classical 2d position + orientation of a wheeled mobile robot in an embedded environment.
Sensor measurements include:
IMU (6axis accl+gyro) @ 40Hz
...
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Is Luenberger observer applicable in practical systems?
I have tried to find out about this from quite a few sources but it still remains unclear to me. I know that the Luenberger observer is applicable for a deterministic system with known control inputs ...
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Rotate sensor frame to body frame
I'm working with a lsm303agr from ST. Here is the frame attached to the chip
Here is the body frame
So I have some doubts about the rotations, before to fuse data ...
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Questions about sensor fusion with Lidar - Extended Kalman Filter
I am attempting to teach myself sensor fusion as I suspect I'll need to do this down the road with lidar and some other sensors. In all my research so far it sounds like a version of the extended ...
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what exactly is 'observation model' for a robot
In my journey to understand the Kalman filter, I understood how a state model representation is derived for a robot and why(to get the robot state for a given input u) it is required.
$$
\boldsymbol{...
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Confused with EKF Localization
I have been trying to understand EKF localization from Probabilistic Robotics by Thrun Burgard and Fox.
There the covariance prediction is given by
$$\overline{\Sigma }_t=G_t\Sigma_{t-1}G^T_t+V_tM_{t-...
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Why is the EKF approximated this way?
I'm a student that recently started taking a course on cognitive robotics. The book I use is Probabilistic Robotics by Thrun Burgard and Fox.
In the EKF algorithm, we linearized the action model in ...
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Simulate GPS IMU With Quadcopter Swarm?
I have multiple drones work in swarm formation, i made the quadcopter model and the swarm one. Until now i have the swarm moving in a formation leader-follower and track a predefined trajectory based ...
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How to fuse IMU with encoders in EKF
Background
I have a car-like mobile robot (4 wheels, where the forward ones are steering wheels) and I want to estimate its pose and velocity assuming 2D planar motion. I'm trying to solve this ...
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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:...
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Would it make sense to use the unscented transform for linear problems too?
I've just learned about the unscented Kalman filter and I have a theoretical question. Suppose our innovation and measurement processes are linear but we know the initial state covariance and/or the ...
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Motion/System Model for range finder
I have a 1D Time-of-Flight based range finder that returns distance in mm. I am trying to implement a Kalman filter to get outlier-free estimation. The sensor measures the distance to the ground below ...
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Localization by comparing current lidar scan with previous lidar scan
I have managed to use an ICP algorithm to produce a relative pose difference between a new lidar range scan and the previous lidar scan. When I tested it on individual scan pairs, the results look ...
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How to derive the kalman gain with the form of K=Pxz/Pz?
please see the formula and reference in the page https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/10-Unscented-Kalman-Filter.ipynb
Traditional formula of gain is expressed ...
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Kalman filter problem with the output
i want to use kalman filter to estimate my phone position, the measurments data is at this point just the accelerometer and the sampling rate is 3ms, i used the library pykalman, i have also wrote my ...
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robot_localization not fusing imu data
According to the documentation in : http://docs.ros.org/en/noetic/api/robot_localization/html/state_estimation_nodes.html
I was able to transform the imu data header fram from "imu_link" ...
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Does the Bayes-Filter perform a convolution in the prediction step?
I am watching the (fantastic) SLAM lectures of Claus Brenner, where he introduces the Bayes-Filter (Kalman-Filter, Particle-Filter, Histogram-Filter).
He says, that the prediction step involves the ...
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Mapping IMU readings from body frame to navigation frame
I'm trying to combine IMU displacements with the time of flight sensor readings in order to navigate through the indoor environment with a non-linear Kalman filter variant. In the graphic below, I ...
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How to calculate the covariance and gain in SLAM when only one measurement is available?
I am trying to perform SLAM for cases where only one sensor measurement is available.
For example, suppose I want to track the position of a robot moving in a room with multiple known landmarks (2D ...
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Can an Xbee transceiver module be used for controlling a stable Quadcopter?
I would like to use an Arduino Nano IOT as a flight controller and connect this to a Xbee transceiver module for control. If the Xbee module was set up so that for each packet transmission it included ...
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Sensor fusion with extended Kalman filter for roll and pitch
I'm trying to implement an extended Kalman filter to fuse accelerometer and gyroscope data to estimate roll ($\phi$) and pitch ($\theta$). I've found a lot of kalman filter questions but couldn't find ...
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GPS + IMU data and kinematics equations
I have the following data
Longitudinal acceleration, $a_x^{IMU}$
Lateral acceleration, $a_y^{IMU}$
Vertical acceleration, $a_z^{IMU}$
Yaw angle, $\psi$
Yaw rate, $\dot{\psi}$
Latitude, $\rightarrow ...
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robot_pose_ekf won't publish any messages
I am having trouble getting the robot_pose_ekf package to publish messages. I launch it with this launch file.
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What would be a way to estimate IMU noise covariance matrix?
Weirdly enough, my robot platform which has an official ROS package supported by a manufacturer doesn't provide any covariance matrices of its sensors. So, I'm basically trying to estimate these ...
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UKF for a serie of observations with covariance
I have some doubts about how to implement a UKF-like algorithm when I only have motion observations and no control inputs.
Assume I have a robot with state $s_t = (x_t, y_t, \theta_t)$ and the ...
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Nonlinear Sensor Fusion with Space-Time Finite Element and Static Condensation?
I have recently implemented an algorithm for the nonlinear fusion of GNSS, barometer, magnetometer, accelerometer and gyroscope data.
The algorithm is based on a space-time finite element where the ...
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How to actually fuse sensor using Extended Kalman Filter
Background
I'm working on 4-omniwheel mobile robot. It have encoder on each wheel and MPU 6050 IMU. The robot positioning suffer a great error because slip, so i try to increase the accuracy of ...
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Drone lost traj recovery
So I am using slam algorithm to localize the drone which is gps denied . The input to the slam algo is imu data and a video .
Now after the first run of the slam algorithm it creates the trajectory ...
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No difference between UKF and EKF for SLAM
I built EKF and UKF SLAM algorithms. The problem is that I expected to see a difference because of the more precise approximation of the system in the UKF.
Here's a screenshot from the estimated path ...
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Kalman filter for visual tracking of a ball sliding on a gutter
I'm working on a project where a robot needs to keep a ball at a desired position on a gutter. The gutter is fixed at one end and held at the other end by the robot’s ...
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Fusing cross-correlated measurements for mobile robot's localization using unscented kalman filter (ukf)
I'm currently working on a mobile robot's indoor localization. On the perception side, I can only rely on a 2D lidar and wheel odometry.
I have used these sources as input of different localization's ...
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GPS Course vs IMU Course
Im currently working with Kalman Filter for position and velocity, one of the important parameters that im using is the heading that the sensor fusion of the imu gives me, but i have seen that the GPS ...
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Kalman Filter with multiple inputs
Let's say I have one laser scanner and a radar device, which I should use to measure a distance to a wall (Fig. 1). Both devices are place on the same support, so... they should measure the same ...
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Particle Filter for IMU tilt angle and bias estimation from Kalman Filter models
I understand the functioning of Particle Filters from the book Probabilistic Robotics and the robotics course provided by Cyrill Stachniss.
I want to implement, from scratch, a particle filter to ...
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IMU-Camera Senor Fusion
I am working on fusing IMU and Camera Sensor Fusion for the Drone to precisely land on the target location.
With the Camera, I am tracking the April Tag which is on the ground. This gives me the x,y,z ...
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Kalman Filter Design
I'm new to Kalman filter design and I'm struggling to understand how to apply the Kalman filter methodology to my problem. I've read a research paper which seems to describe what I'm trying to do ...
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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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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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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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