This is part of a continuing series on diagnostics tooling for the mjbots quad series of robots.  The previous editions can be found at 1, 2, 3, 4, and 5.  Here, I’ll cover the first extension I developed for tplot2 to make it more useful to diagnose dynamic locomotion issues.

Background

Diagnosing problems on robots is hard.  The data rates are high, sensing is imperfect, and there are many state variables to keep track of.  Keeping track of problems that are related to erroneous perception are doubly challenging.  Without a recording of the ground truth of an event, it can be hard to even know if the sensing was off, or if some other aspect was broken.  Fortunately, for things the size and scope of small dynamic quadrupeds, video recording provides a great way to keep a record of the ground truth state of the machine.  Relatively inexpensive equipment can record high resolution images at hundreds of frames a second documenting exactly where all the extremities of the robot were and what it was doing in time.

In previous posts, (1, 2, 3, 4), I covered the updates I made to the underlying serialization and log file format used in mjlib and the quad A1.  This time I’ll talk about the graphical application that uses that data to investigate live operation.

History

You might note the “2” in the name and realize that yes, this is the second incarnation in the mjmech repository, tplot being the initial.  The original tplot.py was a largely a one-day hack job that glued together the python log bindings I had with matplotlib.  It provided a time scrubber, a tree view, and a plot window where any number of things could be plotted against one another.

I used Dear Imgui for the simple Mech Warfare control application I built earlier and was relatively impressed with the conciseness with which one could develop effective (although not necessarily the prettiest), interactive and response user interfaces in C++.  For some time I had been planning on developing a new diagnostic application for the mjbots quad that would allow plotting like the original tplot.py, but would also integrate recorded video and 3D rendering and diagnostics.  I had assumed I would use HTML/JS because it is the cool new thing, but I never got up the energy to make it happen, because every technical step along the way had big hurdles.  I figured I would give Dear Imgui a try, but the big thing it was missing was plotting support.