8
votes
Accepted
What is a good approach for outlier rejection during real time data filtering?
It is both acceptable and standard to use camera observations with a Kalman filter if you are talking about landmark positions in pixel or real-world space. Pixel space observations are usually ...
7
votes
Accepted
How to localise a underwater robot?
Localization under water was always a problem in ocean robotics as electromagnetic signals do not propagate very well in water. I think your best localization sensor in that case would be the good old ...
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
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 ...
6
votes
Accepted
Kalman Filter GPS + IMU
This is a complete re-working of the answer I had originally provided. If you're curious, you can check the edit history and see what was posted earlier.
In comments to this question, OP stated that ...
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 ...
5
votes
Accepted
Robot localization without any sensors
If you know the wheel radius and the speed of the robot, you will be able to calculate its location at any time relatively to its initial position.
...
5
votes
How can my robot find its position in any given map without GPS, including when the initial point is not given?
Determining your location when you have a map but not your starting location is a job for a particle filter.
(Wikipedia's entry on particle filters is not very helpful to beginners.) See also, ...
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
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
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
Image based 3d position estimation with one camera
One camera gives you no depth information, so you have to have some information about the scene before you start (a priori).
The most common way to handle this is with structured light, where you ...
4
votes
How to localise a underwater robot?
If it's actually underwater, how about a webcam looking at the tile pattern on the floor? (Could be considered "cheating" as it will obviously fail in a natural lake, for example.)
You can find a ...
4
votes
How to localise a underwater robot?
One of the prime sensors for global localisation on land is GPS. This is not an option underwater because electromagnetic waves get absorbed quickly.
There are however alternatives, which provide ...
4
votes
How to have a 'Auto Go Home' feature, like the DJI Phantom 3, on a project built quadcopter?
I would go with one of two-ish methods to do this, but both methods require the craft to know its own position. You could do this with GPS, or an IMU, or any other means or combination of position ...
4
votes
Localization of a Robot to find it Coordinates according to the Known Map
Particle filter
According to the OP a robot with at least a distance sensor is available and a map too. That's a nice starting point for developing a hypothesis tracker aka particle filter. At first ...
4
votes
How does fast slam creates grid maps?
Grid based FastSlam relies on the same principle that Landmakr based FastSlam. The difference is that we are not working with each grid cell as a landmark, but the whole gridmap itself.
For Grid ...
4
votes
Accepted
Integrating GPS into Graph SLAM (how orientation fixed?)
You can use a very low information matrix value at the orientation elements of your state, given that the information matrix is the inverse of the covariance matrix.
The covariance matrix ...
4
votes
Accepted
Understanding and implementing belief space planning
The kalman filter that you've already been using on single robots can be broadened to apply to the swarm of robots. If you previously represented the state of a single robot with 5 variables, and you ...
4
votes
Process noise and Measurement noise in Kalman filter
Basically, the relative magnitude between process and measurement noise determines how much to trust a new sensor measurement. In one extreme, if the process noise is zero the kalman filter will ...
3
votes
Image based 3d position estimation with one camera
It is possible to use one camera for 3d position estimation but it is significantly more difficult.
Depth/distance data must be obtained to generate the 3d representation and several techniques have ...
3
votes
Accepted
Position estimation from photo fingerprinting
What you're looking for is called an optical flow system: a camera that by recognizing the movement of patterns can estimate the movement of the camera target relative to the camera. You can ...
3
votes
Determining a robot's distance from a certain point when the robot's position is constantly changing
If you know the position of the point at the begin, an easy solution would be to implement Dead Reckoning using the encoder value. Knowing the position of the robot at time t, compare it to its ...
3
votes
In EKF-SLAM, why do we even need odometry when there is a more reliable sensor?Also, are all SLAM algorithms feature-based?
Just to add up on this, using odometry to estimate the robot position is much faster than using data from a laser scanner. In most situations, data from a range scanner is handled as a 2D PointCloud. ...
3
votes
How to localise a underwater robot?
If you cannot use a camera the task is nearly impossible with your money limitations.
Professionals use a scanning sonar like the tritech micron and a particle based localization like [3] based on ...
3
votes
Multi-Rate Sensor Fusion using EKF
Part 1. Use one or the other. Often odometery is used instead of kinematics or dynamics for prediction, at least in my work.
Part 2.
This is handled by the construction of the measurement equation ...
3
votes
Plotting location using wheel encoder data
A few things:
I took a look at your data set. Did you make sure you used the time column correctly? The first entry is "1429481388546050050" without the decimal. To make it in seconds, it should be ...
3
votes
Linearize a non linear system
The short answer to this question is that linearization won't work, and here's why:
Differential drive robots can be modeled with unicycle dynamics of the form: $$\dot{z}=\left[\begin{matrix}\dot{x}\\...
3
votes
Accepted
Localising a robot placed at an unknown position in a known environment
The problem is that you can't apply path planning until you know where the robot is in the global coordinate frame. There are many localization techniques, and each has its pros/cons; I have used ...
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Related Tags
localization × 281slam × 77
mobile-robot × 73
kalman-filter × 49
mapping × 35
ekf × 31
particle-filter × 29
ros × 27
odometry × 19
gps × 19
sensors × 17
navigation × 17
sensor-fusion × 16
lidar × 15
imu × 14
arduino × 10
cameras × 10
quadcopter × 9
probability × 9
computer-vision × 7
gyroscope × 7
algorithm × 7
pose × 7
kinematics × 6
wheeled-robot × 6