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Thu, 25 Jan 2007

progress report - Python console and neural nets

Sorry for not reporting sooner - we have a number of ongoing projects, so rather than leaving everyone in suspense, here's a progress report ...
  • New Python-based console for SRV-1
    We have a test version of the update for pySRV1Console - it works well on some systems, but has synchronization problems on other systems. Rather than holding onto this any longer, we are making a test version available, and would welcome feedback from users on how it performs - you can post feedback on the Surveyor Robotics Forum. Here's the download link:


    On systems where it works well, pySRV1Console is providing a video frame rate which is close to performance of the Java-based SRV1Console. The issue with Internet Explorer has been resolved, so this version should work with any browser, and the image processing commands are almost 100% functional.

    If you want to run from source (, you'll need Python 2.4 and the PySerial package ( If you have Python installed, the console is started with:

          python -com /dev/cu.SLAB_USBtoUART
          python -com COM4

    If you don't have Python installed, there's an pySRV1Console.exe which should run on Windows without any Python libraries installed. The command line parameters are the same as the Java SRV1Console, with one addition: '-com' to specify the com port string:

          pySRV1Console -com COM4

    Once it's running, the main console page is:


    We hope to have any remaining performance issues resolved in the next week or so, and in the mean time, we welcome your feedback.

  • Neural Nets
    As discussed here a few weeks ago, we have been looking at ways to add adaptive / emergent behavior capabilities to the core functions of the SRV-1. It's still too early to report any significant breakthroughs, but we have produced some useful test results with simple backpropagation neural networks for color and shape classification, and we're currently exploring how we might also employ self-organizing-maps (SOM) as an alternative or in combination with backpropagation networks. It is clear that we will be able to integrate core neural network functions into SRV-1 firmware - the main challenge is working out the structure of the commands and flow of data through the SRV_protocol and built-in commands for the C and BASIC interpreters. My goal is to have a version of firmware available for testing some basic neural net functions in a few weeks.

    Posted Thu, 25 Jan 2007 14:25 | HTML Link | see additional stories ...