So I finally got some time to provide the updated info for my rasp bot. In this post, I give updates on how I have rebuilt the bot to have drive more accurately (the last version with such small wheels did not fair so well on different surfaces and the motors were not great) and I talk about the SPI enhancements for speed control and voltage read back.
The new build:
1.) a left and right servo for the wheels
2.) much larger wheels
3.) a wooden chassis to hold bread board and camera
I learnt during the upgrade, that wood and elastic bands are really good materials to use during building custom projects. Wood because it's relatively easy to form and elastic because you can hold the different pieces together easily without having to glue everything permanently. Later you can then reconfigure things with ease.
In this version, I switched back to a mini bread board, so that I can add things to the circuit more easily. The last version was all soldered together, which was great fun, but really not practical in the long run when you are still trying things out. For the motors, I bought some servos, which are normally intended for controlled angler movement, but I removed these circuits and restrictions. Then I use them as plain DC motors with gear. I liked this solution because the servos were relatively cheap and provide good power. The big wheels I found a model shop around the corner. They are pretty much directly attached to the servos (the servos came with small plastic discs that I could glue to the wheels with a CD providing a in surface between the wheel and the servo disc attachment). This is also really nice because was quite difficult to find a simple gear system for connecting a DC motor to wheels. Mostly others buy a remote toy and modify that because then all the parts are pretty much there. However, you are not able the to build your own design.
Lastly, I now have the new raspberry pi camera. It's great for use with raspivid and streaming. You can get great video and choose your compression(a problem when you only have 440KB/s dsl uploads). That's all stuck or bound together as shown in the picture.
Speed control and voltage read back:
I was having some issues with capturing the video and analysis thereof when moving. The issue Is that with movement it takes a while for the stream to settle. Otherwise there is just to much noise or blurred images(especially in low light) to make reliable descisions). one solution is to make the movement less jerky, as up until now I was just turning the motor on and off (with an input voltage of 4.8v). I did reduce the input to just 3.6, which helped, but still was not good enough. So I changed the code to send a speed value to the atmega with every movement control. The atmega then uses this value to toggle the time which the enable pin of the hbridge(L293), so that it is only on a certain percentage of the time. This is basically software PWM (pulse wave modulation). The atmega does this by counting loop cycles and switching the enable pin on for the number of loop cycles sent from the python script running on the PI. I could also use the atmegas PWM pins, but those conflict with the SPI pins (the MSO and SS pins are 2 of the 3 PWM pins).
I have updated the source
https://github.com/arcanon/raspbot/blob/master/Blink.ino and the python script,
https://github.com/arcanon/raspbot/blob/master/ardspi.py. The SPI read back is done by using the quick2wire duplex method. Note that 1 byte from the slave is read back at the exact same time as 1 byte from the master. This means the slave needs to pre-prepare the data to be sent or you discard the first byte. I have just done the later for now. I send back the 10 bit conversion of the voltage measured by the adruino on a pin which is connect to the positive battery supply of the motors (3.6V) via a 10K resistor. The same connection is connected via another 10K resistor to ground. The voltage is then measured at 1.8V, divided as expected. I have not done time measure measurements to see how this varies over time.
The python script also contains some networking code, which I will write about in another post. That code allows the PI to take to a server which is capturing the video stream (from raspivid) and then doing various video analysis. I can then make use of a dekstop GPU to improve the speed of the analysis for object detection and such.
