LIDAR on the new guy

Not really anything new, but I moved the LIDAR to the new PiPlate after RoboNUCs disassembly.  It only took a few minutes to re-use the old code in the new application.


To be honest the old interface, while really cool looking, was getting out of hand.  So I am trying to not do that again.  This program will be visualization and testing only (ala RVIZ).  I will do the Navigation planning in a separate application. OpenCV is off the table for the moment, too buggy and … This chassis will be for SLAM, no open CV needed.  A second RoboMagellan style will be built, using the RPi and probably a PIXYCam (although at the moment, also too buggy in Linux), and so it will have a very different UI (Python something), although this UI will still function for remote visualization.



“And then Git happened. Git is so amazingly simple to use that APress, a single publisher, needs to have three different books on how to use it. It’s so simple that Atlassian and GitHub both felt a need to write their own online tutorials to try to clarify the main Git tutorial on the actual Git website. It’s so transparent that developers routinely tell me that the easiest way to learn Git is to start with its file formats and work up to the commands. And yet, when someone dares to say that Git is harder than other SCMs, they inevitably get yelled at, in what I can only assume is a combination of Stockholm syndrome and groupthink run amok by overdosing on five-hour energy buckets.

Here’s a tip: if you say something’s hard, and everyone starts screaming at you—sometimes literally—that it’s easy, then it’s really hard. The people yelling at you are trying desperately to pretend like it was easy so they don’t feel like an idiot for how long it took them to figure things out. This in turn makes you feel like an idiot for taking so long to grasp the “easy” concept, so you happily pay it forward, and we come to one of the two great Emperor Has No Clothes moments in computing.”

Sad realities, Happy new trails

I am at a bit of a crossroad and I need to choose a path.

I started RoboNUC to learn slam. I still want to learn SLAM but along the journey to get there I made a few discoveries (as you should in a learning endeavor).  RoboNUC was not physically all I hoped it would be with a few design flaws (first time with laser cutting etc). And I could not buy components that would do what I wanted. I had to design, wire and solder and program some electronics myself (no I DO NOT think this is what robot building should be about).

The second item lead me to explore making what I wanted for myself, in a form that I could offer others, thus the new products.  I also designed a new chassis with some lessons learned.  This has been a full time effort, but I like what is emerging from it.

So I need to decide, when the effort winds down, do I resume SLAM on RoboNUC, or do I move SLAM to the new robot? At the moment I am liking the potential on the new robot more. Its onboard computer will be a Pi with linux, which is not my favourite dev platform, but if all goes well, I mount a XBee shield on the Pilot and I can remote from my desktop or a laptop, which is a much better SLAM learning configuration, and switch between that and the Pi fairly easy. And the SLAM lessons are in python, so if I do use the Pi, I should already have a lot of the code. Pretty compelling.

With that RoboNUC will be donating parts to the new bots and I hope their story is just as informational (yes their, I have 3 sets going now, mine and 2 other people are planned so far).  The BOM is also public (as was RoboNUC)

Bill of Materials

TL;DR   RoboNUC $1000 with Intel I5.   PiPlate $280 with Pi.

I really hope to kit the new one, and price will be a little higher (I’ve got to make something) but if you want to duplicate the effort yourself, under $300 for a serious robot platform I think is uber reasonable! Comparable to Arduino Robots I would think, and a lot more powerful. The intent is, for $280 + a pixy cam ($80), you have a RoboMagellan capable robot. You still need to add some coding, but a lot of the startup, hardware, electronics and plumbing software is done and ready to be used. Anyone who wants to try Seattle Magellan (or maybe anywhere) with one of these gets a free T-Shirt.


yeah, I really did get some T-shirts :|

Importing STL to Helix3D

“ROS was a mixed bag for me. Like Spiked3, I found those dependency issue, too. I like Gazebo and the ROS data visualizers, but everything seemed like a step back in time.”

Helix3D is an awesome 3D toolkit on top of the already native 3D support in WPF.  In windows 8, you don’t use DirectX or OpenGL windows in your applications (although you can if you want); your application IS a DirectX window. This offers high speed optimized user interfaces, with native 3D support, not as an after thought but as the basis of.


So in my robot visualization application, I needed to import the model of the robot.  It took a while to find the bits and pieces (Helix3D has very limited documentation at the moment, other than the source code) and here is what I found and put together;

Update 2/15; So as I learn a little more about Helix 3D I realize the above is not optimal, but it works and conveys the idea.


Robotics, hahaha