This Project aims to synchronize Desktop environment running on one panda board with another panda board over Wi-Fi. The project involves segmentation of the desktop using the effective algorithm and segmented information is structured in custom format. The output of the algorithm is then encoded with the help of efficient encoding method to minimize the need of network resources. The encoded output is sent over Wi-Fi using RTP towards another Wi-Fi terminal, which can decode the input data stream and appropriate display is created. All the changes in the senders display are identified and corresponding changes are transmitted so that only modified information is sent over Wi-Fi to show relative changes on receiver’s end.
A system using PANDABOARD that can stream complete user interface information of one unit to another display unit over Wi-Fi.
Use PANDA to create and maintain ad-hoc cloud to provide platform as a service. Today in the
era of smart phones and tablets having a hardware constraint to run any application residing in
your machine is a major drawback. So consider a scenario where you are traveling (Bus/Trains/
Flight), where there are several phones/computational devices, of which while some are highly
active, some may be totally dormant, thus wasting a lot of processing power when there is a need
for it. So having a single PANDA as a controlling device (cloud server) , all the platform could
register itself to the cloud to provide its computational capabilities (also to use), thus acting as a
CPU hot-plug to add more cores to PANDA as and when they register , thus creating an ad-hoc
cloud system dynamically without any additional resources. With good load prediction algorithm
in place, Applications can be launched in this multi-core system, without having to worry about
the device's own processing power.
< AVR On The Go >
A small, portable AVR programmer*.
*: The programmer shall have a small screen, micro keyboard, autonomous power source and ISP(6/10)pins and JTAG connections to connect with the targets.
It would be on running an embedded Linux distribution and have an environment setup for compiling C/C++ & ASM code for the AVR.
I wish to use the Pandaboard as the main brain for a bipedal robot.
So far I've managed to natively compile ROS( Willow Garages Robotic Operating System) using the latest version DiamondBack and Ubuntu Natty Netbook.
Those instructions can be found here.
APEX is a bootloader for embedded systems. It was originally written to support the Sharp LH series of processors but has been ported to a number of additional ARM targets such as the Samsung S3C24xx series.
* Easy to build. It depends only on shell utilities and GCC.
*Easy to configure. There is a single configuration file and it uses the linux-2.6 Kconfig infrastructure.
*Excellent dependency management. Uses Linux kernel Kbuild to optimally manage dependencies.
*Modular. Commands and drivers may be included or excluded by configuration.
*Supported targets: LH79520, LH79524, LH7A400, LH7A404, IXP42x (e.g. Linksys NSLU2), S3C24xx, and iMX31.
*Support for RARP IP configuration and TFTP transfers to the target.
*Filesystem drivers for FAT, EXT2, and JFFS2.
*Partition driver for FIS as used by Redboot.
*Small footprint. A limited feature version can be as small as 16KiB.
*Support for booting APEX from non-memory-mapped storage, e.g. NAND flash, OneNAND, I2C
*OMAP3 and OMAP4 support under development(no need for separate MLO and bootloader)
Team Graviton is a contestant in the SFE international Autonomous Vehicle Competition 2012. Our vehicle is equipped with a computer vision system in addition to high precision spatial orientation sensors. This sophisticated realtime computer vision system, artificial intelligence and blistering fast vehicle makes Team Graviton unbeatable.
It's a part of ArabBSD project which has a goal to port OMAP4 to FreeBSD.
This project is to create virtualization on OMAP4430.
A slim syslink API inspired by gst-dsp.
The main objective of this project is to build a cheap auto-focus camera using OpenCV libraries.
- 5 MP Auto-focus camera module.
- Runs on linux with custom user interface.
- Social-oriented (Upload pictures directly to communities like Facebook, Photobucket, Picasa, Flickr, etc.).
- Community based development.
- Media Player.
OpenCV is a widely used, cross-platform real-time image processing libraries. The key applications of OpenCV include Facial Recognition System, Gesture Recognition and Motion Tracking which are sufficient to provide functionalities we find in regular cameras like Face Detection, Smile Detection, image stabilization, different shooting modes (like Panorama, smile shot, continuous shots, etc.), etc.
The user has full access to code thereby allowing him to tweak the existing code or write new ones. Wrappers for languages like C#, Python, Ruby and Java are already developed. Therefore code can be written in any language. Also code written by community members can accessed and downloaded. The downloaded code can be installed in the camera. This allows the user to upgrade his camera to better functionality.
Further, this can be used as a Media Player. Also functionalities like Geo-tagging can also be implemented if the board has a built-in GPS.