Spacecraft inspection robot

As we contemplate long-term manned missions to Mars and beyond, we need a convenient way to inspect and repair the damage to spacecraft caused by micrometeorites, space debris, and radiation. I designed a robot for this purpose with a team of fellow students in the excellent Human Spaceflight class taught by former astronaut Mike Massimino. The robot is designed to be a companion for spacecraft and space habitats like the International Space Station, and can be deployed to inspect the exterior of any structure in microgravity.

The robot is cube-shaped with thrusters at the center of each face and an omnidirectional antenna. It also has a camera at the center of each face, and their video feeds are stitched together to form an immersive view of every direction surrounding the robot. Piloting the robot is supposed to be very easy to learn, and would consist of setting a direction in the immersive view and pressing go/reverse at different speeds. Finally, one face also has precision and infrared cameras, a trace gas analyzer, and a flashlight, to closely inspect damaged areas. When the robot is not being used, it can rest and recharge in the airlock.

I created a simulation of the robot in the ISS environment to train prospective pilots. Interestingly, it runs pretty well on iPhones (20 MB download), but collision detection is slow even on desktops.

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Tempofy: rhythm-matching shuffle

This is a project I worked on with a team at PennApps in winter 2015. It finds random songs on Spotify matching the tempo of your movements according to the iPhone's accelerometer.

I did the iOS programming, but it currently requires a backend Flask server to be running to calculate bpm and use the Echonest API.

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Stratus: bluetooth chat

Wouldn't it be cool if you could chat with strangers around you in a coffee shop, or even around an entire campus? A couple friends and I thought so, and we made a bluetooth chat app for Android phones during Columbia's ADI hackathon.

It's a fun proof of concept, and hopefully in the future we'll figure out some decentralized protocol like Bittorrent for phones to communicate over. This could be useful for people in disaster areas when cell towers get damaged, or in very crowded places where networks get overloaded.

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Graphing your Facebook network

This is a tool to make a force-directed graph of your Facebook friend network. Each friend is represented as a node, and is connected to each of your mutual friends. Each time this page is loaded, my friends pull each other together, as though they were connected by springs, in a physical simulation that results in a final balance. Highly connected groups pull each other close and will end up the way I group my friends in my mind: clustered around schools, towns, events, and organizations. This is what my network looks like:

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Tracking space usage at Columbia

During the last finals week of my junior year, an interesting website came online at density.adicu.com. It tracks the number of devices connected to WiFi access points at many places on campus, and translates these numbers into a crowdedness metric (100% := full, 0% := empty). The website, however, only shows the crowdedness at the instant you access it. ρ(t) is a tool I made while procrastinating during finals week that scrapes data from the website every 15 minutes and shows it using a D3 plot. It's not a smart solution now since there's an API, but it can show you how to scrape a website.

Above is what ρ(t) recorded during finals at Columbia. The largest fluctuations are between daytime and nighttime (although a fair number of people stay active at Butler, the 24-hour library). We can also see on most days a swell in activity after lunchtime. In my experience, finding a spot in the library was impossible just after lunch.

And we also see the beautiful, gradual death of finals week over three days.

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Plotting the Mandelbrot set

Motivation

This mesmerizing video Dr. Odden showed before class one day.

Background on the Mandelbrot set

The Mandelbrot set is a fractal. In fractals, large-scale shapes and patterns can be seen at much smaller scales (see how the bubble to the left of the cardioid looks like the smaller one to its left, and so on?). This gif shows it well.

Black: in the Mandelbrot set. White: outside the set.

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