I just realized that the latest Wordpress update had messed up the embedded video on the Bongopong page. I fixed it, so you can laugh along with me (at me).
On a side note, the biggest thing I heard about that project was that it looked too hard. Rest assured that it was difficult because I was using a DIY Bongoboard and the skateboard deck has a concave bottom – coupled, of course with my complete lack of coordination and balance.
My wife got me a real Bongoboard for Christmas this year, and it’s 100 times easier to use. I may have to bring this one back. With a left/right moving game like breakout and a stable board, I think this could be a lot of fun.
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Hack a ThinkGeek R/C Moon to display realtime phase changes
0 Comments | Posted by Tim in Uncategorized
I just finished my latest hack. I modified a ThinkGeek R/C Moon Phase light so that it reflects the current lunar phase in realtime.
Essentially, the R/C Moon Phase light is a nightlight that comes bundled with an infrared remote control. The controller allows the user to change the moon’s current phase with the press of a button – or automatically cycle through the standard phases of the moon throughout the day.
I decided that it would be more interesting if the model moon actually reflected the current phase of the moon based on the date. I did this by replacing the original PCB with an arduino and aDS1307 realtime clock module from Sparkfun. The DS1307 module maintains the proper time and date, while the arduino calculates the current phase of the moon based on the date. The RTC module contains a coin cell battery backup that enables the internal clock to maintain the proper time, even without power, for up to 17 years!
I also included a simple C# application for Windows.NET that updates the DS1307 in case it starts to drift over time.
Check it out at www.imagitronics.org/rc-moon/
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Some very nice python routines that read NMEA GPS strings and transmit them over UDP.
I had a chance to sit down a play around with the Maxbotics LV-EZ3 ultrasonic range finder. The EZ3 is a low cost, reasonably high quality range finder capable of measuring distances from around 6″ all the way up to 254″. The device is fairly straightforward and can output analog voltage, PWM, or serial data (although strangely, RS-232 not TTL). The analog output is the obvious choice, as I will be using my arduino board to interact with the device.
When I initially connected the device I was mildly discouraged. The values returned on the analog pin seemed slightly erratic. Too much so to even process a data sample. The MaxSonar-EZ1 FAQ recommended implementing a low pass RC filter using a .1uF capacitor and 1k resistor, which stabilized the output nicely.
The next step was to convert the data into inches so that it will be more useful to Terry. Analog voltages on the arduino range between 0 and 1023 and are scaled based on the analog reference input. The default analog reference is 5V. This means that 5V applied to the arduino’s analog input pin is interpretted by the arduino as 1023. The arduino also has the ability to use an internal analog reference of 1.1V on the ATMega168 microcontroller (2.56V on ATMega8) or an external reference that can be specified by applying voltage to the arduino’s AREF pin. Information on the arduino analog reference configuration can be found here. The Maxbotics EZ3 outputs a maximum of 5V, therefore I was able to use the default reference.
With the low pass filter functioning properly and the analog reference properly set, I was ready to convert the output into inches. The arduino analogRead reference page indicates that each unit (0-1023) represents 0.0049V, and the Maxbotics LV-EZ3 datasheet specifies that an inch is represented by 9.8mV (0.0098V). From there it was simple to translate the arduino’s analog input into inches: ((units * 0.0049)/0.0098).
The code seems to work flawlessly. The data doesn’t seem to vary 
beyond an inch in either direction even without data sampling and when the unit is jostled around. I will, however, likely sample the data using a mode average that will return the most frequently occurring value in a given dataset. Tomorrow I will try to uncover an effecient algorithm for this, even though it’s completely usable as-is.
These little wall racers look like an incredibly fun side project to pass some time when not working on the autonomous vehicle project.
Fritsl, from letsmakerobots.com retrofitted these little RC cars with some artificial intelligence that allows them to race around any room in your home. The cars are designed to ride counter-clockwise along the wall simulating a standard oval track.
I would really love to make a half-dozen of these things with various levels of AI aggression and watch them battle it out around the house. You can peep the video of the little fellas in action at letsmakerobots.com
