One day while sitting in class in a Cornell University schoolroom, [Will] and [Michael] thought how cool it would be to send text messages to each other via their Texas Instruments calculators. Connecting the two serial ports with a serial cable was out of the question. So they decided to develop a wireless link that would work for both TI-83 and TI-84 calculators.
The system is powered by a pair of ATmega644’s and two Radiotronix RF Modules that creates a wireless link between the two serial ports. The serial ports are 3 wire ports, which can be used for several things, including acting as a TV out port. [Will] and [Michael] reverse engineered the port’s protocol and did an excellent job at explaining it in full detail. Because they are dealing with the lowest level of the physical protocol, there is no need for them to deal with higher levels like checksums, header packets, ext.
Be sure to stick around after the break to see a video of the project in action. It’s quite slow for today’s standards. If you have any ideas on how to speed it up, be sure to let everyone know in the comments.
Continue reading “Send Wireless TXT between Two TI Calculators”
Though this project uses an RC helicopter, it’s merely a vessel to demonstrate a fascinating machine learning algorithm developed by two Cornell students – [Akshay] and [Sergio]. The learning environment is set up with the helicopter at its center, attached to a boom. The boom restricts the helicopter’s movement down to one degree of motion, so that it can only move up from the ground (not side to side or front to back).
The goal is for the helicopter to teach itself how to get to a specific height in the quickest amount of time. A handful of IR sensors are used to tell the Atmega644 how high the helicopter is. The genius of this though, is in the firmware. [Akshay] and [Sergio] are using an evolutionary algorithm adopted from Floreano et al, a noted author on biological inspired artificial intelligences. The idea is for the helicopter to create random “runs” and then check the data. The runs that are closer to the goal get refined while the others are eliminated, thus mimicking evolutions’ natural selection.
We’ve seen neural networks before, but nothing like this. Stay with us after the break, as we take this awesome project and narrow it down so that you too can implement this type of algorithm in your next project.
Continue reading “Self-Learning Helicopter Uses Neural Network”
A team of students from Cornell University are looking into alternative ways of creating a security system that can be locked or unlocked by using physical gestures in an enclosed space.
It is the final year project for [Ankur], [Darshan] and [Saisrinivasan] in their MEng of Electrical and Computer Engineering. The system prototype is capable of recording a gesture and then comparing the gesture with future gestures to lock or unlock the system. Consider it like a secret handshake to get into the office!
To analyze the gesture they are using four SparkFun proximity sensors setup in a linear array to sense the distance a hand is moved. An ATMega1284P is used to convert the analog sensor signal to digital for further processing. The project is extremely well documented, as it appears to be the final report for the project.
A short video after the break shows off the prototype and gives a good explanation of how the system works.
Continue reading “Gesture Based Security Lock”