Questions tagged [ekf]
the extended Kalman filter, a filter for nonlinear state estimation.
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Visualizing and debugging an EKF
I am currently debugging and tuning an EKF (Extended Kalman Filter). The task is classical mobile robot pose tracking where landmarks are AR markers.
Sometimes I am surprised how some measurement ...
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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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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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How exactly does sensor fusion work in Kalman filters?
I've been looking into implementations of Extended Kalman filters over the past few days and I'm struggling with the concept of "sensor fusion".
Take the fusion of a GPS/IMU combination for example, ...
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innovation step ekf localization?
Let's say we have a bunch of observations $z^{i}$ from sensor and we have a map in which we can get the predicted measurements $\hat{z}^{i}$ for landmarks. In EKF localization in correction step, ...
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Paradox: I can't use accelerometer measurements to obtain information about my states in a quadcopter?
I'm currently developing an EKF to estimate the position and orientation of a quadcopter. My state vector is comprised of 3D position, 3D velocity, 3 euler angles and the angular velocity vector.
...
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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 ...
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How do you determine EKF process noise for pre-recorded data sets?
I've seen this question, which asks about determining the process noise for an EKF. I don't see anything there about pre-recorded data sets.
My thought on how to determine the noise parameters, ...
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Mahalanobis distance between 2 line features
I am implementing the ATLAS SLAM framework for a ground robot, using EKF Slam for local maps and using line segment features. The line segment features can be abstracted to their respective lines <...
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the uncertainty of initializing new landmark in EKF-SLAM
In EKF-SLAM (based-feature map) once the robot senses a new landmark, it is augmented to state vector. As a result, the size of the state vector and the covariance matrix are expanded. My question is ...
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Plotting location using wheel encoder data
Context: I am working with the SFU Mountain Dataset [http://autonomylab.org/sfu-mountain-dataset/]
The UGV image - via the SFU Mountain Dataset website:
I have used the following state update ...
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GraphSLAM equation doubt
I have question about GraphSLAM implementation.
To find out the path and map using GraphSLAM we rely on this equation:
$$\mu=\Omega^{-1}\xi$$
where $\Omega$ is our information matrix which ...
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How to avoid matrix singularity in GraphSLAM
I am trying to implement GraphSLAM from Sebastian Thrun's paper, The GraphSLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures.
When I compute the inverse of my information ...
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Calculate the uncertainty of a 6-dof pose for graph-based SLAM
This question is strongly related to my other question over here.
I am estimating 6-DOF poses $x_{i}$ of a trajectory using a graph-based SLAM approach. The estimation is based on 6-DOF ...
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EKF-SLAM initialize new landmark in covariance matrix
I am trying to implement an EKF-SLAM using the algorithm for unknown correspondences proposed in the book "Probalistic Robotics" by Sebastian Thrun in Table 10.2 .
By now I understand actually all ...
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Implementing ESKF
I'm currently struggling with implementing the Multiplicative Kalman Filter or Error State Kalman Filter as described by Landis Markley in Attitude Error Representations for Kalman Filtering. Sadly ...
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EKF-SLAM: Shrink covariance matrix on one direction
I have implemented an EKF on a mobile robot (x,y,theta coordinates), but now I've a problem.
When I detect a landmark, I would like to correct my estimate only on a defined direction. As an example, ...
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Multi-Rate Sensor Fusion using EKF
Context: I have an IMU(a/g/m) + Wheel Odometry measurement data that I'm trying to fuse in order to localize a 2D (ackermann drive) robot.
The state vector ...
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EKF SLAM and Mahalanobis distance?
So far I have done EKF Localization (known and unknown correspondences) and EKF SLAM for only known correspondences that are stated in Probabilistic Robotics. Now I moved to EKF SLAM with unknown ...
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Choosing the state vector for an EKF
Could someone help me understand the logic behind choosing a particular state space vector for an EKF?
Context: Say there is a 4 wheeled robot that operates only in 2D. It is equipped with an ...
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How is gyroscope bias exposed and tracked?
For an accelerometer, the measurement is defined in the following way:
$$a_m = R_w^b(a_{w} - g) + b_a + v_a$$
Where $R$ is a rotation matrix, $g$ is gravity, $v_a$ is noise, and $b_a$ is the bias. ...
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Direct vs semi-direct methods for visual inertial odometry
I was reading these papers on visual inertial odometry from IROS 15:
Semi-Direct EKF-based Monocular Visual-Inertial Odometry
Robust Visual Inertial Odometry Using a Direct EKF-Based Approach
I ...
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sparse matrix in EKF SLAM
I've successfully done with EKF Localization Algorithm with known and unknown correspondences that are stated in "Probabilistic Robotics". The results make perfect sense,so I can estimate the position ...
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EKF localization known correspondences
I'm facing problems with this book and it is the only book that discusses localization in depth. The results that I'm getting makes no sense. I've read a lot of papers, majority of them copy the ...
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What's the correct approach to merging of localization and odometry data?
We've got a mobile platform with a source of odometry and an IMU, which are merged in an EKF filter (robot_localization node), producing continuous odom->base_link transform. The robot is also ...
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Confusion of EKF equations
I read Probabilistic Robotics by Sebastian THRUN (online version). I also read http://ais.informatik.uni-freiburg.de/teaching/ws12/mapping/pdf/slam04-ekf-slam.pdf
Question1 :
What will be the ...
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Having a hard time understanding this equation in monocular EKF SLAM
Reading this paper on visual odometry, where they have used a bearing vector to parameterize the features. I am having a hard time understanding what the state propagation equation for the bearing ...
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Multiple EKFs or one big
Let's say I would like to use an EKF to track the position of a moving robot. The EKF would not only estimate the position itself but also variables affecting the position estimate, for example IMU ...
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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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How is the GPS fused with IMU in a kalman filter?
I've been trying to understand how a Kalman filter used in navigation without much success, my questions are:
The gps outputs latitude, longitude and velocity.
While the IMU outputs acceleration and ...
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how to plot $\pm 3 \sigma$ of a landmark in EKF-SLAM
I have implemented 2D-SLAM using EKF. The map is based-feature in which there is only one landmark for the sake of simplicity. I've read some papers regarding this matter. They plot the $\pm3\sigma$ ...
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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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Why innovation equation in Extended Kalman filter is called innovation?
In the Extended Kalman filter for SLAM, why is the innovation equation called so? Is there a reason for using the specific word "innovation" for the difference between the observed ...
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The uncertainty is big while the sensor is rather accurate at measuring a landmark in EKF-SLAM
I've a 2D sensor which provides a range $r$ and a bearing $\phi$ to a landmark. In my 2D EKF-SLAM simulation, the sensor has the following specifications
$$
\sigma_{r} = 0.01 \text{m} \ \ ,\sigma_{\...
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extended kalman filters, linearization of output
Say, we are dealing with an odometric localization problem.
In the below example, $(x_k, y_k), (x_l, y_l)$ are cartesian coordinates of the sensor and the landmark respectively. Then the output ...
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Tracking vehicle 6 states extended kalman filter required?
I'm trying to track an accelerating vehicle using a camera, an IMU, and a GPS.
I use for the state space equation a constant acceleration model:
The states are the position, the velocity, and the ...
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Maximum likelihood estimator (ML Data Association) EKF
This question is an extension to my previous problem (Data association with ekf). My problem here is in the line 16 in the aforementioned link.
16. $ j(i) = \underset{k}{\operatorname{...
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Confused with EKF Localization
I have been trying to understand EKF localization from Probabilistic Robotics by Thrun Burgard and Fox.
There the covariance prediction is given by
$$\overline{\Sigma }_t=G_t\Sigma_{t-1}G^T_t+V_tM_{t-...
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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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How to perform active search in point feature based monoSLAM?
I am modifying an implementation of SLAM with single camera, MonoSLAM [1]. Instead of image patches, I want to use features points (ORB) to track landmarks. MonoSLAM uses a EKF framework. So for ...
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Doubt with linearization and discretization process - Ekf
In the paper "State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU", the authors describe the application of an extended kalman filter to estimate states of a quadruped ...
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EKF localization data association
I am working with ROS indigo and clearpath huskyA200 and wanted to implement the EKF localization with unknown correspondences with my own hokuyo lidar data for a school project. Giving the algorithm ...
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GPS/ 1GYRO - 2D + ACCEL+GPSEKF
I am trying to integrate GPS and IMU but as a first step I am trying to use just 1d gyro and 2d accelerometer to work. Below is my model -
State model and propagation
So, my question is .. after ...
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EKF SLAM (prediction of new landmarks)
Prediction of new landmarks are commonly expressed as:
Xm = Xr + r*cos(phi + theta_r),
Ym = Yr + r*sin(phi + theta_r)
However this is only true ...
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EKF Localization when robot is in parallel with a landmark.
I'm facing a real weird problem with EKF Localization. The filer gives me wrong error every time the robot is in parallel with a landmark. I've debugged the code many times but failed to solve the ...
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Data association with ekf?
Given part of the following algorithm in page 217 probabilistic robotics, this algorithm for EKF localization with unknown correspondences
9. for all observed features $z^{i} = [r^{i} \ \phi^{2} \ ...
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SLAM without data association?
I would like to build 2D EKF-SLAM in openGL. I've implemented the entire virtual environment in which there is a robot that moves in 2D and there are some landmarks(feature-based map). I have the ...
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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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Landmark extraction algorithm
The landmarks are often used in SLAM. What are the algorithms used to extract them, and how can a robot differentiate the landmarks, if they detect one in point A at Xt and another in Xt+1? How can ...
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Need help in implementing EKF based SLAM
I just started learning about slam and I have been trying to simulate a robot moving around a set of landmarks for the past 3 days. The landmarks have known correspondences.
My problem is, if I add ...
