Help with making a custom Dashboard and the Rectangular Target Processing

[The Trooper]

I am a senior this year in my club, but I only have been programming since last year. I can do a lot of the basic programming with the WPI robotics library, and simple tasks, but I have not gotten a clear answer, or have been shown how to incorporate anything into a custom dashboard. There are examples and tutorials out there, but these leave a lot of information out, and some do not even work when I use them. I would just like some guidance, and see how I can incorporate the image from the camera that recognizes the rectangle, and how I can incorporate what the camera sees and if it recognizes it when the cRIO is up an running. I haven't even been able to figure out how to tell it to look for light intensity within the cRIO project. I don't know if it is or not. Here are my main goals:

• See the black and red image side by side with the non-processed image on the dashboard
• Adjust the camera to look for light sensitivity within the cRIO project
• Figure out how to incorporate my own data into the dashboard

There has got to be an easier way to do it than the example that NI provides for you. I am to the point where I do not know what to do anymore, and with being in a region where there are only two teams in my area, mine and one other that is just about as young as we are, I do not know where else to turn.

I will gladly appreciate any help anyone can give me

[bstites82]

I haven't worked much with custom dashboards myself, but I would suggest playing with/reading carefully through the rectangular target tracking example. while it runs on the crio and not the dashboard it is an excellent learning tool. open the rectangular target tracking robot main vi. change the crio ip address and then click run while connected to the robot. then open the front panel of the vision vi and enable the original image and processed image displays. NI provides a huge amount of control with this example and the controls can be adjusted in real time to find the best parameters for your robot. once those are found you can change controls to constants. once you've gotten familiar with the example code you will find that you should know how to:
See the black and red image side by side with the non-processed image on the dashboard
Adjust the camera to look for light sensitivity within the cRIO project
your third goal requires you to mesh the example with your dashboard and figure out how to send data back and forth from the robot to the dashboard. there are several threads on data transmission using tcp or udp so that should give you an idea where to start. hopefully this helps.

[dbeckwith]

We've had some success creating a custom dashboard. All you really have to do is find the gigantic cluster of constants in the sample dashboard program and replace that with your own cluster of datatypes. Once you do that, you can send a cluster of matching types from your robot code and it will show up on the dashboard. In the dashboard VI you would just replace all the default indicators with your own. Our team doesn't use LabView (we use Java) so we don't know much else about it, but we've been able to customize the dashboard pretty well. It would be very cool to see the processed camera image in the dashboard, if you figure out how to do that, could you share what you did?

[Greg McKaskle]

There is a tutorial that steps you through the example and explains how to incorporate and debug. Have you gone through the tutorial?

If you have already incorporated the vision code into your project, I'd next run by pressing the Run Arrow, so that you can probe the images and values. This is far easier than rebuilding your dashboard each time you want to view something new.

If you are past that stage and want to update the dashboard, you need to place new indicators and connect them to data coming from the robot. But, sending arbitrary images back is harder as they will not fit in the high or low priority status data. That part is far easier to do with probes. It is pretty easy to send the target data back and draw that over the camera image which the dashboard receives directly from the camera.

Please give more info and ask questions specific to the step you are on. It is important to have everything planned out, but in terms of helping you out, it makes it hard to know which step you need immediate help with.

Greg McKaskle