16
votes
Accepted
What is inverse depth (in odometry) and why would I use it?
Features like the sun and clouds and other things that are very far off would have a distance estimate of inf. This can cause a lot of problems. To get around it, the inverse of the distance is ...
15
votes
Accepted
Difference between Rao-Blackwellized particle filters and regular ones
The Rao-Blackwellized Particle Filter (RBPF) as you say in your question performs a marginalization of the probability distribution of your state space.
The particle filter uses sampling to ...
11
votes
What is inverse depth (in odometry) and why would I use it?
The inverse depth parameterisation represents a landmark's distance, d, from the camera exactly as it says, as proportional to 1/d within the estimation algorithm. The rational behind the approach is ...
11
votes
Accepted
What does Simultaneous Localization And Mapping (SLAM) software do?
Localization is the process of estimating the pose of the robot the environment. Number 5 in your list. Mapping is estimating the position of features in the environment. Number 1.
2, 3, and 4 are ...
8
votes
What is the difference between SAM and SLAM?
SLAM is the process of locating oneself in a totally unknown environment where you are simultaneously mapping your environment and plotting your position in that environment. SAM is a technique used ...
7
votes
Accepted
the uncertainty of initializing new landmark in EKF-SLAM
You can use the Jacobians of the inverse observation model to initialize the new row/column of the covariance matrix.
Suppose your observation model is $g(\mathbf{x})$, which maps your state $\...
6
votes
Accepted
Which micro-controler/processor to be used for autonomous stereo vision robot system?
Stereo vision and SLAM are pretty heavy algorithms, both in terms of the processing power and RAM required. You can forget about running this on a little microcontroller like an Arduino. These run at ...
6
votes
Accepted
What is the difference between Positioning and Localization Systems
In my opinion, the main difference is :
Positioning : gives information about the robot coordinates. It gives raw data that you can use.
Localization : it is the process of the robot (or other actor) ...
6
votes
SLAM: Why use two cameras (stereo) if SLAM can be done using single camera (monocular)?
The most important point is the scale. If you do monocular SLAM, your map will only be accurate up to scale so that you e.g. cannot compute the length of the travelled path in meters. The scale ...
6
votes
Which is a good and cheap 3D LIDAR or other options?
There are now some sub and around ~1000USD 3D Lidars available. I wanted to provide an answer for future reference if anyone else comes looking for "cheap" Lidars.
LeddarTech M16 ~500 USD ...
6
votes
What's the difference between Pose Measurement and Position Measurement?
what you are looking for is written in the paper. Position refers only to x,y,z translational measurements while pose means position and orientation.
5
votes
Accepted
Build a ROS robot with SLAM without laser
A kinect mounted on your robot is enough for mapping and localization. There are a few different packages that will work:
rgbdslam can create a 3d map using a kinect
You can use ...
5
votes
Accepted
EKF SLAM and Mahalanobis distance?
The value of $\alpha$ is just some threshold Mahalanobis distance.
Let's say you have four entries in your map. You take a measurement, then you calculate four predicted measurements (one for each ...
5
votes
Accepted
role of chi2 in SLAM back-end optimization
Specifically, the Chi-Square Distribution(or Chi2, $\chi^2$, or equivalently $\chi^2_1$) is used to model the probability of the absolute value of the deviation of the measurement from it's expected ...
5
votes
SLAM : Why is marginalization the same as schur's complement?
The following are mostly based on "Factor Graphs for Robot Perception" by Frank Dellaert and Michael Kaess, with additional notes:
As a reminder, marginalization is about having a joint ...
5
votes
Accepted
In the SLAM for Dummies, why are there extra variables in the Jacobian Matricies?
From the paper:
$\begin{bmatrix} range\\bearing \end{bmatrix} = \begin{bmatrix} \sqrt{(\lambda_x-x)^2 + (\lambda_y - y)^2 } + v_r \\ tan^{-1}(\frac{\lambda_y-y}{\lambda_x-x}) - \theta + v_{\theta} \...
5
votes
Accepted
Are there any advantages to using a LIDAR for SLAM vs a standard RGB camera?
My question: are there cases where you'd still need a LIDAR or can
this expensive sensor be replaced with a standard camera? ...
A each one of them has its advantages/disadvantages. Thus in some ...
5
votes
Difference between SLAM and Localization
Localization is always done with respect to a map.
SLAM(Simultaneous Localization and Mapping). As it is in the name, also does localization with respect to a map. The only difference is that the ...
4
votes
Is there any advantage to velocity motion models over odometry motion models for SLAM?
I can't think of a reason why a velocity model (based on control commands)
would be superior to an odometry model (which uses the actual wheel speeds).
The lecture notes from Freiburg on motion ...
4
votes
Absolute positioning without GPS
I know this is an old question but I will just add a bit to the currently existing answers. First, this is a very complex problem that everyone is trying to tackle, including google with their Tango ...
4
votes
What is inverse depth (in odometry) and why would I use it?
Davison's paper introducing the method is easy enough to understand:
Inverse Depth Parametrization for Monocular SLAM by Javier Civera, Andrew J. Davison, and J. M. Martınez Montiel DOI: 10.1109/TRO....
4
votes
Hector SLAM, Matching algorithm
Imagine someone put you in a wheelchair and blindfolded you, then let you reach your arm out and touch a wall. You could tell how far away the wall was, but as long as you were pushed parallel to the ...
4
votes
How to use SLAM with simple sensors
The actual implementation of SLAM won't care about whether you are using high fidelity laser range finders or cheaper ultrasonic sensors. Both are providing range measurements with the biggest ...
4
votes
FastSlam 2.0 Implementation?
I suggest you to give a look to Sebastian Thrun's work here. In fastSLAM (both 1.0 and 2.0) each particle maintains an array which contains the states of the landmarks as well as the robot's states. ...
4
votes
Accepted
SLAM : Why is marginalization the same as schur's complement?
See the walk-through
The Schur complement helps with the closed form derivation but isn't necessary. It's just a nice convenient property of Gaussians and the covariance matrices.
In these papers,...
4
votes
Understanding Drift in Simultaneous Localization and Mapping (SLAM)
Your intuition is mostly correct. Returning to where you started and re-observing landmarks you mapped earlier is called closing the loop in the SLAM literature. As you mentioned, your uncertainty ...
4
votes
Pose-Graph-SLAM: How to create edges if only IMU-odometry is given?
First off, it doesn't sound like you're actually doing SLAM. You didn't mention an exteroceptive sensor (e.g., laser, camera) that actually maps the environment. With just an IMU, you are doing ...
4
votes
What's the difference between the term "pose estimation" and "visual odometry"?
It is also often the case that the author lacks knowledge, makes mistakes, or is adding unnecessary statements to their work. Just because it is published does not make it true.
In this case though, ...
4
votes
Difference between SLAM and "3D reconstruction"?
You are right about the sameness of SLAM and 3D reconstruction. At the same time I don't think the author is misclassifying.
The english is a little non-standard. The author could have better said it ...
4
votes
Accepted
Suggestion for relevant non-complex simulator
just use matlab or and python with a set of fixed features in space represented as points. Don't do any vision processing. At this point any vision processing would be overkill.
you are making this ...
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