Inspiration

Recent natural disasters, like the devastating earthquake in Indonesia, continue to illustrate the necessity and dangers of the jobs of first responders. Often, when searching for missing persons after such disasters, first responders put themselves in harm's way. It is clear that a device that allows us to rapidly and accurately assess first responders' surroundings and guide them towards the safest path of rescue is needed in such situations.

What it does

SRIRACHA (The Search and Rescue Informatic Robot Assisting in Charting Hazardous Areas) is a modified RC tank mounted with an oscillating range-finder. This allows it to construct 3D points clouds of buildings as it navigates through them.

How we built it

SRIRACHA is powered by an Arduino Mega which communicates with a Node.JS server via Bluetooth. This serial communication is parsed with JavaScript and is displayed visually through Pixi.JS.

Challenges we ran into

We encountered several issues with setting up serial communication with the robot. Through many different libraries and APIs, we managed to find a solution using SerialPort. This allowed us low-level access to the Bluetooth hardware (a HC-06), letting us stream data off the robot in real time.

Accomplishments that we're proud of

Creating our own communication protocol for our robot has inspired us in the elegance of networking. Designing the protocol, we learned about the fundamentals how we can make comprehensible communications between computers and microprocessors.

What we learned

We learned the value of mentorship during SD Hacks. The amazing mentors that helped us debug Node.JS file streaming and strategized with us on how to best communicate wirelessly with our robot helped us in focusing our intentions towards productive ventures, and allowed us to learn in a collaborative environment.

What's next for SRIRACHA

We would like to add functionalities for optimal path-finding with the implementation of A* algorithm. This would allow the robot to be smarter about where it moves to best optimize its point cloud generation.

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