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7 votes
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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 $\...
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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 ...
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5 votes
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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. ...
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5 votes
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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 ...
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  • 960
5 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 ...
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  • 960
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 ...
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4 votes

How does 3D Lidar work?

Lidar, sonar, and radar all work generally the same: Emit a pulse. For radar, this means briefly energizing an antenna. For sonar, it means briefly energizing a sound transducer/speaker. For lider, ...
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4 votes

Occupancy grid maps

As the wikipedia page of Occupancy grid mapping explains, the result of the mapping process is a binary 1 or 0, occupied or not, the decision itself may be based on noisy data, which involves the ...
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3 votes
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How to approach an object

I wasn't totally sure what you meant by "draw and arc and check where the arc is on valid map position. Then move the robot there and calculate the angle to rotate the robot". Perhaps you mean ...
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  • 6,337
3 votes

Mahalanobis distance between 2 line features

There are many ways to measure the statistical difference between two distributions. For your case, you might consider the Bhattacharyya distance. From that page, the Bhattacharyya distance $D_B$ is $...
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  • 960
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. ...
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3 votes

What is the most appropriate SLAM algorithm for quadrotors with RGB-D camera?

I assume that your target environment is indoors as you use RGB-D camera. When you want to use it with quadrotor, you need high update rate for accurate pose estimation. Some packages that you can ...
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3 votes
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how to plot $\pm 3 \sigma$ of a landmark in EKF-SLAM

What you are referring to is plotting the estimate with the uncertainty bounds - in particular the $3\sigma$ ($\pm3$ standard deviations) bounds which corresponds to 99.7% probability that the true ...
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3 votes
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How does information gain based exploration differ from frontier based?

Frontier based exploration is concerned primarily with exploring the physical space in order to produce an occupancy grid (or cost map) of the terrain traversibility. The control actions follow a set ...
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  • 872
3 votes

A sensor that can see glass/transparent objects and surfaces

Unless you need very good resolution or a very tight detection pattern, I would go with an ultrasonic sensor. They can be very cheap and easily meet your detection range specs, for the very low end ...
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  • 1,909
3 votes
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A sensor that can see glass/transparent objects and surfaces

I'm pretty sure that a very basic IR proximity sensor would do the trick. Glass is opaque to all but visible light. IR (as well as UV) will not penetrate the glass and you ought to be getting reliable ...
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  • 1,027
3 votes
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3D mapping using only a 2D Lidar

I don't think what you're asking is possible with the state of the art sadly. You cannot, AFAIK, generate a 3D map from a hand held 2D LIDAR without any other sensors. It's a very interesting question ...
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  • 561
3 votes

3D mapping using only a 2D Lidar

That is an already solved problem. As Squelsh mentioned CSIRO released its initial version in 2009 and their work is commercialized by GEOSLAM already. One of a CMU student released a open source ...
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  • 1,375
3 votes

World and Map Frame for a real robot

As you've figured, static transforms are valid for fixed offsets such as sensor positions. They are the minimal solution the more complete recommended solution is to setup a robot model. There's ...
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  • 1,184
2 votes

how to plot $\pm 3 \sigma$ of a landmark in EKF-SLAM

Unless I misunderstood what you're trying to show on this plot, you want to essentially plot your estimate (or, in this case, the estimation error) with its 3 standard deviation bounds. What you have ...
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  • 21
2 votes
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joint compatibility branch and bound (JCBB) data association implementation

Suppose you have three measurements (1, 2, and 3) and four landmarks (a, b, c, d). The joint compatibility is a measure of how well a subset of the measurements associates with a subset of the ...
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  • 960
2 votes
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Can mapping be done in real life applications without also solving the localization problem at the same time (i.e. SLAM)?

First off, occupancy grid mapping is just one possible representation of a map. I think your question really applies many map representations. Here are my thoughts. Mapping without SLAM Whether or ...
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  • 960
2 votes

Mapping formats for small autonomous robots

I really don't think the format matters, so I'd suggest you go for what's most convenient to you. You might want something that can be displayed easily on screen, any bit map format will do. You ...
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  • 1,021
2 votes

using range-only sensors for mapping in SLAM

SLAM is so huge topic with a lot of challenging problems. For beginners, I don't really recommend you to read papers. The authors of academic papers assume you know not only the basics in the field ...
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  • 2,349
2 votes

Is it possible to do SLAM with few IR sensors like Buddy?

I did casually search for something like this a year or two ago. "Sparse sensing" or "sensing limited" were the sort of phrases that cropped up. Kris Beevers has some interesting publications in this ...
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  • 1,021
2 votes

Autonomous Indoor Positioning System Robot based on CV approach

The camera should work fine as long as you can easily find the rover in the environment. An easy way to accomplish this is to place two different colored markers on the rover. By finding the markers ...
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2 votes

Understanding and correct drift when using BreezySLAM (aka tinySLAM / CoreSLAM)

You'll find that Gmapping works a lot better. I have used core slam quite a bit with the 04lx, tweaked the code, and tuned the algorithm. It works in a lot of cases, but... If you really want to ...
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2 votes

Understanding and correct drift when using BreezySLAM (aka tinySLAM / CoreSLAM)

Till now this is the easiest SLAM implementation that I've found. It works pretty well, however, there is a lot of room for improvement using the same principle used in the original code online. "1- ...
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  • 309
2 votes

How can I implement tremaux algo in arduino line follower to navigate and create map?

I would highly recommend using the encoders over estimating travel distance by rpm + time. Estimating motor velocity is notoriously tricky. Especially at slow speeds. A direct measurement is ...
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  • 5,245
2 votes
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Path of the robot

One of the ways to do path tracking is by indoor mapping. In indoor mapping you can use Triangulation method. Basically, this method uses the help of Relative Received Signal Strength (RSSI) from ...
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