Depth Perception

[ianonavy]

We have decided on a robot design that requires sensing how far the basketball hoops are from our robot, but we are not sure how to go about doing that. We were thinking about mounting the Kinect on our robot, but that proved to be a lot more complicated than we expected. I've read some posts here about using lasers to detect how far the hoops are. How would our team go about doing that? What is the simplest/easiest way of going about doing this?

tl;dr; What's the easiest way to sense how far away the basketball hoops are from the robot?

Thanks for your input, good luck on your build season!

[andreboos]

You could use the ultrasonic range sensor in the Kit of Parts.

[DoctorWhom93]

If you open up the Video Processing LabVIEW example it has a function defined in there called "Distance". You can open that up and get what FIRST put in their for processing distance using the camera

[DuaneB]

Note that maximum range of the Maxbotix LV-MaxSonar®-EZ1 sonar range finder is 254 inches (21 ft / 6.5m).

[KennyLives]

Originally Posted by DuaneB

Note that maximum range of the Maxbotix LV-MaxSonar®-EZ1 sonar range finder is 254 inches (21 ft / 6.5m).

This little guy came in the KOP and works pretty well. I say use it.

[plnyyanks]

You could use the axis camera instead of the kinect and process the image to determine the distance. If you have LabVIEW, one of the examples shows how to do this. Otherwise, these threads might be useful, along with this whitepaper.

[ianonavy]

Well, we're going to be programming in either C++ or Java, so LabVIEW is out of the question. I don't understand how you could process an image to determine depth with a single image. Wouldn't it be more accurate to have two cameras to have stereo vision?

[plnyyanks]

Attached is a screenshot of the LV example VI. If you don't use LV, then just pay attention to the triangles drawn out on the bottom.

We can calculate the distance from the target using a couple known values and some trigonometry. We know the camera's resolution, its field of view (the angle at which it can view, or 2Θ), and the width of the target in real life, and the target's position in the camera image. Here's a comment from the VI that goes over the math:

Since we know that the target width is 2', we can use its pixel width to determine the width
of the camera field of view in ft at that working distance from the camera. W is half of that.
Divide by the tangent of theta (half the view angle), to determine d.

So we take the width of the target box in pixals, and determine the width of the whole image (2/width*xresolution/2). Then, we can divide that by the tangent of .5Θ (where Θ = the view angle, as found on the Axis camera datasheet [about 47˚ for the M1011, and 54˚ for the 206]) to get the distance in feet.



Also, all this is explained in NI's Whitepaper on the subject

[rich2202]

It gets a little more complicated when you are looking at the basket from an angle. You have to examine the shape of the square to calculate the viewing angle. Then use the viewing angle to adjust the size of the box before calculating the distance.

[windtakers]

Originally Posted by plnyyanks

Attached is a screenshot of the LV example VI.

where is this example at in labview

[landybr]

[Tylernol]

We're currently using the axis camera to find the rectangle of the reflective tape. We'll analyze the aspect ratio of the square, then count the pixels to find our distance.

...or at least that's what our programmers told me. I'm not one myself and most of it is very confusing to me.

:edit Oh, and we're using Java. I could probably ask our programmers for the code.

[nssheepster]

Our team wants to do that, but upon reflection and research, we feel that the camera or "laser" sensing method is not consistently reliable enough. We thought of a filtered gyroscope - accelerometer system, but we don't have the time and manpower to finish it before our first regional. So, we are doing without. But reliability is going to be a problem, no matter what almost - incomprehensible algorithms you use.

[Dale]

Be sure to test how well the ultrasonic sensors work in a noisy environment. What happens when a robot with a chain driven wheel turning at 5000 rpm is next to your robot or when your own shooter is running. It may work fine, it may not! We're going to test that today.

[DonRotolo]

Originally Posted by Dale

Be sure to test how well the ultrasonic sensors work in a noisy environment.

Excellent idea. Other robots may have similar sensors pinging as well.

In any case, it is possible to reduce much of the potential/actual interference using standard audio techniques.