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Because my robot’s control system runs on a LabVIEW real-time machine, I have no recourse but to add new features in LabVIEW. Oh, I tried coding new stuff in C++ on another computer and streaming information via UDP over gigabit, but alas, additional latencies of just a few milliseconds are enough to make significant differences in performance when your control loop runs at 2 kHz. So I must code in LabVIEW as an inheritor of legacy code.
With a computer engineering background, I find that having to develop in LabVIEW fills me with dread. While I am sure LabVIEW is appropriate for something, I have yet to find it. Why is it so detestable? I thought you’d never ask.
- Wires! Everywhere! The paradigm of using wires instead of variables makes some sort of sense, except that for anything reasonably complex, you spend more time trying to arrange wires than you do actually coding. Worse, finding how data flows by tracing wires is tedious. Especially since you can’t click and highlight a wire to see where it goes – clicking only highlights the current line segment of the wire. And since most wires aren’t completely straight, you have to click through each line segment to trace a wire to the end. [edit: A commenter pointed out double clicking a wire highlights the entire wire, which helps with the tracing problem]
- Spatial Dependencies. In normal code, it doesn’t matter how far away your variables are. In fact, in C you must declare locals at the top of functions. In LabVIEW, you need to think ahead so that your data flows don’t look like a rat’s nest. Suddenly you need a variable from half a screen away? Sure you can wire it, but then that happens a few more times and BAM! suddenly your code is a mess of spaghetti.
- Verbosity of Mathematical Expressions. You thought low-level BLAS commands were annoying? Try LabVIEW. Matricies are a nightmare. Creating them, replacing elements, accessing elements, any sort of mathematical expression takes forever. One-liners in a reasonable language like MATLAB become a whole 800×800 pixel mess of blocks and wires.
- Inflexible Real-Estate. In normal text-based code, if you need to add another condition or another calculation or two somewhere, what do you do? That’s right, hit ENTER a few times and add your lines of code. In LabVIEW, if you need to add another calculation, you have to start hunting around for space to add it. If you don’t have space near the calculation, you can add it somewhere else but then suddenly you have wires going halfway across the screen and back. So you need to program like it’s like the old-school days of BASIC where you label your lines 10, 20, 30 so you have space to go back and add 11 if you need another calculation. Can’t we all agree we left those days behind for a reason? [edit: A commenter has mentioned that holding Ctrl while drawing a box clears space]
- Unmanageable Scoping Blocks. You want to take something out of an if statement? That’s easy, just cut & paste. Oh wait no, if you do that, then all your wires disappear. I hope you remembered what they were all connected to. Now I’m not saying LabVIEW and the wire paradigm could actually handle this use case, but compare this to cut & paste of 3 lines of code from inside an if statement to outside. 3 seconds, if that compared to minutes of re-wiring.
- Unbearably Slow. Why is it when I bring up the search menu for Functions that LabVIEW 2010 will freeze for 5 seconds, then randomly shuffle around the windows, making me go back and hunt for the search box so I can search? I expect better on a quadcore machine with 8 gb of RAM. Likewise, compiles to the real-time target are 1-5 minute long operations. You say, “But C++ can take even longer” and this is true. However, C++ doesn’t make compiles blocking, so I can modify code or document code while it compiles. In LabVIEW, you get to sit there and stare at a modal progress bar.
- Breaks ALT-TAB. Unlike any other normal application, if you ALT-TAB to any window in LabVIEW, LabVIEW completely re-orders Windows Z-Buffer so that you can’t ALT-TAB back to the application you were just running. Instead, LabVIEW helpfully pushes all other LabVIEW windows to the foreground so if you have 5 subVIs open, you have to ALT-TAB 6 times just to get back to the other application you were at. This of course means that if you click on one LabVIEW window, LabVIEW will kindly bring all the other open LabVIEW windows to the foreground, even those on other monitors. This makes it a ponderous journey to swap between LabVIEW and any other open program because suddenly all 20 of your LabVIEW windows spring to life every time you click on.
- Limited Undo. Visual Studio has nearly unlimited undo. In fact, I once was able to undo nearly nearly 30 hours of work to see how the code evolved during a weekend. LabVIEW on the other hand, has incredibly poor undo handling. If a subVI runs at a high enough frequency, just displaying the front-panel is enough to cause misses in the real-time target. Why? I have no idea. Display should be much lower priority than something I set to ultra-high realtime priority, but alas LabVIEW will just totally slow down at mundane things like GUI updates. Thus, in order to test changes, subVIs that update at high frequencies must be closed prior to running any modifications. Of course, this erases the undo. So if you add in a modification, close the subVI, run it, discover it isn’t a good modification, you have to go back and remove it by hand. Or if you broke something, you have to go back and trace your modifications by hand.
- A Million Windows. Please, please, please for the love of my poor taskbar, can we not have each subVI open up two windows for the front/back panel? With 10 subVIs open, I can see maybe the first letter or two of each subVI. And I have no idea which one is the front panel and which is the back panel except by trial and error. The age of tabs was born, oh I don’t know, like 5-10 years ago? Can we get some tab love please?
- Local Variables. Sure you can create local variables inside a subVI, but these are horribly inefficient (copy by value) and the official documentation suggests you consider shift registers, which are variables associated with loops. So basically the suggested usage for local variables is to create a for loop that runs once, and then add shift registers to it. Really LabVIEW, really? That’s your advanced state-of-the-art programming?
- Copy & Paste . So you have a N x M matrix constant and want to import or export data. Unfortunately, copy and paste only works with single cells so have fun copying and pasting N*M individual numbers. Luckily if you want to export a matrix, you can copy the whole thing. So you copy the matrix, and go over to Excel and paste it in and……….suddenly you’ve got an image of the matrix. Tell me again how useful that is? Do you magically expect Excel to run OCR on your image of the matrix? Or how about this scenario: you’ve got a wire probed and it has 100+ elements. You’d like to get that data into MATLAB somehow to verify or visualize it. So you right click and do “Copy Data” and go back to MATLAB to paste it in. But there isn’t anything to paste! After 10 minutes of Googling and trial and error, it turns out that you have to right click and “Copy Data”, then open up a new VI, paste in the data, which shows up as a control, which you can then right-click and select “Export -> Export Data to Clipboard”. Seriously?!? And it doesn’t even work for complex representations, only the real part is copied! I think nearly every other program figured out how to copy and paste data in a reasonable manner, oh say, 15 years ago?
- Counter-Intuitive Parameters. Let’s say you want to modify the parameters to a subVI, i.e. add a new parameter. Easy right? Just go to the back panel with the code and tell it which variables you want passed in. Nope! You have to go to the front panel, right-click on the generic looking icon in the top right hand corner, and select Show Connector. Then you select one of those 6×6 pixel boxes (if you can click on one) and then the variable you want as a parameter. LabVIEW doesn’t exactly go out of its way to make common usage tasks easy to find.
Now granted, there are some nice things about LabVIEW. Automatic garbage collection [or rather the implicit instantiation and memory managing of the dataflow format, as one commenter pointed out], easy GUI elements for changing parameters and getting displays, and…………well I’m sure there are a few other things. But my point is, I am now reasonably proficient in LabVIEW basics and still have no idea how people manage to get things coded in LabVIEW without wanting to tear their hair out. There are people who love LabVIEW, and I wish I knew why, because then maybe I wouldn’t feel such horrorific frustration at having to develop in LabVIEW. I refuse to put it on my resume and will avoid any job that requires it. Coding in assembly language is more fun.
Operating rooms are scary places at the best of times, and when going under the knife, you’d like to know that a surgeon’s itchy nose or her morning’s double espresso isn’t going to cause any accidents. This is where medical robotics can ride in to the rescue. As a PhD student developing intelligent surgical instruments, I design algorithms that aid surgeons in procedures. One of the fundamental problems of helping someone is knowing what they are trying to do. Handing a hammer to a construction worker when he is pouring concrete is not terribly helpful.
As in case of convex mirrors for savety vision when driving, here a popular solution is to use computer vision: attach some cameras to the microscope, see what the surgeon is doing, figure out what her goals are, and then provide assistance. For instance, microinjections of veins smaller than a human hair are very useful procedures that are currently too difficult to perform reliably in the operating room. Our tool reduces surgeon tremor and uses image analysis at high magnification to guide the needle into the vein, increasing the success rate of the procedure. Unfortunately, many of the useful algorithms are difficult to perform in real-time. Furthermore, different algorithms are often required in parallel: several methods might track the tip of the instrument, another builds 3D representations of the tissue surface, and still others run analysis to detect and diagnose blood leakages or diseased areas.
Currently, I run a number of algorithms and am forced to make compromises even with powerful quadcore machines. With modest stereo 800×600 resolution cameras that run at 30 Hz, 5 gigabytes of images need to be processed every minute. This increases to upwards of 40 GB/min with high speed or high-definition cameras. Trying to analyze the sheer number of pixels coming is much like the analogy of trying to drink from a fire hose. Simply encoding and saving the video in real-time for post-op review becomes challenging. Consequently, I run tracking algorithms at lower resolutions, sacrificing precision for speed. Diagnoses are performed pre-operatively or manually on demand during pauses in the procedure. 3D representations of the tissue are built initially and updated only infrequently. This affects the level of assistance the system provides to the surgeon.
In fact, significant amounts of my time go towards optimizing C++ or even assembly level code to maximize performance. Reducing L1 cache misses, utilizing branch predictions, and rewriting code to take advantage of SIMD instructions let me run more algorithms and provide better aid to the surgeon. Even with such optimizations, I am still hitting the limits of what four cores can do. However, a most encouraging aspect of computer vision is its often embarrassingly parallelizable nature. With a 48 core machine, I could do a significantly better job. I would move to higher definition video for much greater precision, parallelize my tracking algorithms for enhanced speed, run advanced stereo algorithms for high quality 3D reconstructions, and thus more effectively provide the surgeon with aids that make the operating room a less scary place.
Today was a packed day, full of excitement. As the TA for computer vision, I had to give the lecture today since my professor is in Kyoto at the ICCV conference. My lecture was on SIFT, arguably the most important concept in computer vision. And so many glazed looks from the class….sigh….at least I don’t think it went too poorly. I debated recording it so I could analyze it later to see how badly I did, but didn’t get around to it. Next time….procrastination strikes successfully again. Interestingly enough, the back row was apparently the place to be. I had one friend fall asleep during my lecture and two others were apparently arguing on whether I was a controls or vision person. I personally maintain that I’m neither: while attempting to do both, I do neither well.
I am also working with the new visiting Spainish student in my lab on Kalman Filters and developing a model of Micron. The results so far are looking promising with a very basic Kalman filter with an identity A matrix and no inputs. It is able to filter stationary noise by several factors to an RMSE of 1-2 micros. Not bad, but then again we are using the Kalman filter under the most idealistic scenario. It will be interesting to see what happens when we add in a model of hand movements and the kinematics of the system. On an unrelated note, I spent some time working with Uma to get his new computer which uses PCI instead of ISA to work in the realtime operating system QNX. He is trying to interface with various electronics such as DACs mounted to PCI expansion cards. That still needs more work as we keep getting weird errors where functions compile and link just fine but then spit out “Error not implemented” when you run them. Oddnesses abound.